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BEYOND ARROWS: ENERGY PERFORMANCE OF
A NEW, NATURALLY VENTILATED DOUBLE-SKIN FACADE
CONFIGURATION FOR A HIGH-RISE OFFICE BUILDING
IN CHICAGO
BY
MONA AZARBAYJANI
DISSERTATION
Submitted in partial fulfillment of the requirements
for the degree of Doctor of Philosophy in Architecture
in the Graduate College of the
University of Illinois at Urbana-Champaign, 2010
Urbana, Illinois
Doctoral Committee:
Professor James R. Anderson, Chair, Director of Research
Associate Professor Richard Strand
Associate Professor Ralph Hammann
Professor Ty Newel
ii
ABSTRACT
Designers tend to rely on their intuition when designing naturally ventilated buildings without
detailed analyses for the long term. It may be argued that for many standard and smaller
buildings, designing for natural ventilation is straightforward: a simple process of drawing
diagrams to illustrate how air flows within the building, which can achieve satisfactory comfort
conditions. However, there is a significant lack of information in the current literature to
demonstrate the complexity and challenges in designing large, naturally ventilated buildings.
This is especially true when the new double-skin facade (DSF) configuration is used as a means
of conserving energy while providing superior thermal comfort. For these types of buildings, it
is important to have the tools to evaluate a design‘s predicted performance to achieve successful
natural ventilation concepts.
It has been learned that significant energy saving is possible by exploiting natural ventilation in a
DSF configuration. To determine if a DSF configuration will provide a better thermal comfort
through natural ventilation, this research uses building simulation tools (EnergyPlus) and
Computational Fluid Dynamics (CFD) to analyze various thermal-comfort parameters through
parametric studies in the facade.
This thesis presents three significant contributions for the evaluation of natural ventilation in
high rise office buildings with DSF configuration:
A methodology for assessing the performance of naturally ventilated DSF buildings
through an airflow modeling was developed by three-dimensional analysis using Fluent.
Buoyancy, wind, and combined ventilation strategies for a commercial office building with
an open floor plan layout were evaluated using the k-ε model.
Models to simulate the specific DSF typology and couple the envelope-level results to a
building simulation program.
A framework for comparing and evaluating the conventional facade solution with a new
configuration of naturally ventilated DSF.
iii
Acknowledgements
I would like to thank my advisor, Professor Jim Anderson, Your insight and our discussions were
invaluable in the advancement of this research. I would like to thank Professor Hammann, for his
unfailing guidance and patience throughout my quest to fulfill my research.
I am indebted to my thesis committee members for their support and insight during my research,
and for their time, effort, and encouragement. Your suggestions and consideration was greatly
appreciated.
My thanks and appreciation also go to those who gave up their valuable time and effort to guide,
advise, and teach me, especially Professor Strand, Professor Bill Rose, and Professor Dimitrios
Kyritsis.
I am also thankful to Jeaongli Kim, who patiently resolved and explained my Fluent problems.
I want to be sure to thank the Smart Energy Design Center for the many discussions, laughs, and
moral support through the past four years. In particular, I would like to thank Ben Sliwinski: you
have always been a true friend, willing to discuss and review my research, and have been
supportive throughout.
I would like to thank all the experts who, by making available their theses, reports and articles,
have provided easy access to knowledge.
To my friends, thank you for always listening, supporting, and reviewing my efforts over the past
four years. My brother, you have my gratitude for always pushing me to succeed for being
supportive.
Last but definitely not least, I would like to express my greatest gratitude to my parents for their
support during all the years of my study. I wish to thank them for believing in me and supporting
my choices without considering any cost.
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Table of Contents
List of Figures .............................................................................................................................. viii
List of Tables and Graphs .............................................................................................................. xi
Chapter 1.0 Introduction ........................................................................................................... 1
1.1 Building Energy Use ........................................................................................................ 3
1.2 Problem statements and difficulties ................................................................................. 5
1.3 Goals of this Research ...................................................................................................... 6
1.4 Scope of document ........................................................................................................... 8
Chapter 2.0 Natural Ventilation Strategies ............................................................................. 11
2.1 Introduction .................................................................................................................... 11
2.2 Natural ventilation mechanism: Driving forces ............................................................. 12
2.2.1 Stack pressure: Thermal buoyancy ......................................................................... 12
2.2.2 Wind-driven ventilation .......................................................................................... 16
2.2.3 Thermal buoyancy and wind in combination.......................................................... 18
2.3 Natural ventilation principles ......................................................................................... 21
2.3.1 Single-sided ventilation .......................................................................................... 21
2.3.2 Stack ventilation...................................................................................................... 22
2.4 Elements of Natural Ventilation ..................................................................................... 23
2.4.1 Double facades ........................................................................................................ 24
2.4.2 Chimneys ................................................................................................................ 25
2.5 Natural ventilation and high-rise buildings .................................................................... 26
2.6 Conclusion ...................................................................................................................... 28
Chapter 3.0 Double Skin Facade and Natural Ventilation ...................................................... 29
3.1 Introduction .................................................................................................................... 29
3.2 Definition Single Skin Vs Double .................................................................................. 29
3.3 History and background ................................................................................................. 31
3.4 Overview of the system .................................................................................................. 31
3.4.1 Thermal performance .............................................................................................. 31
3.4.2 Type of cavity ventilation ....................................................................................... 34
3.4.3 Airflow concept ...................................................................................................... 35
v
3.4.4 Partitioning of the facade ........................................................................................ 36
3.5 Previous work ................................................................................................................. 45
3.6 Natural ventilation in double skin facade ....................................................................... 49
3.7 Double skin facades in office buildings ......................................................................... 50
3.8 Conclusion ...................................................................................................................... 51
Chapter 4.0 Application of Computational Fluid Dynamics in Architecture ......................... 52
4.1 Introduction .................................................................................................................... 52
4.2 Application of CFD for building design ........................................................................ 52
4.2.1 CFD approaches in an indoor environment simulation .......................................... 54
4.2.2 CFD approaches in an outdoor airflow simulation ................................................. 59
4.2.3 CFD approaches in facade design ........................................................................... 60
4.3 Simulation approach: Model set up ................................................................................ 62
4.3.1 Fundamental of airflow modeling ........................................................................... 62
4.3.2 Creating a model geometry for CFD ...................................................................... 63
4.3.3 Boundary conditions of the three-dimensional model ............................................ 69
4.4 Solution procedure ......................................................................................................... 71
4.5 Interpretation of CFD results.......................................................................................... 75
4.6 Conclusions of CFD modeling ....................................................................................... 76
Chapter 5.0 Methodology ....................................................................................................... 77
5.1 Introduction .................................................................................................................... 77
5.2 Goals of the research ...................................................................................................... 78
5.3 Developing inputs for the modeling process .................................................................. 80
5.4 Methodology for energy simulation and analyzing results ............................................ 81
5.4.1 Simulation of the base case ..................................................................................... 81
5.4.2 Generation of building alternatives ......................................................................... 83
5.5 Computational Fluid Dynamics ..................................................................................... 83
Chapter 6.0 Energy Performance Assessment ........................................................................ 86
6.1 Introduction .................................................................................................................... 86
6.2 Energy use in office buildings ........................................................................................ 86
6.3 Description of the reference building ............................................................................. 88
6.3.1 Office layouts .......................................................................................................... 90
6.4 Simulation of single skin facade .................................................................................... 90
6.4.1 Input ........................................................................................................................ 91
6.4.2 Output ..................................................................................................................... 94
vi
6.5 Simulation of facade alternatives ................................................................................... 96
6.5.1 Description of double skin facade alternatives ....................................................... 96
6.5.2 Combined shaft-corridor DSF ................................................................................. 98
6.5.3 Energy use simulation results ............................................................................... 100
6.5.4 Impact of enclosure on the perception of thermal comfort ................................... 106
6.6 Summary of the energy use simulation results............................................................. 108
Chapter 7.0 CFD Modeling of the combined shaft-corridor DSF ........................................ 109
7.1 Introduction .................................................................................................................. 109
7.2 CFD modeling .............................................................................................................. 109
7.2.1 Climate data assumptions for the site ................................................................... 110
7.2.2 External airflow modeling .................................................................................... 112
7.2.3 Wind pressure assessment..................................................................................... 114
7.3 The geometry of the CFD model.................................................................................. 115
7.3.1 Model construction materials and components..................................................... 117
7.3.2 CFD model boundary conditions .......................................................................... 117
7.4 Fluent simulation results demonstration ...................................................................... 119
7.4.1 Cavity and room air temperature .......................................................................... 119
7.4.2 Airflow .................................................................................................................. 123
7.5 Analysis of the model solved by Fluent ....................................................................... 129
7.6 CFD result findings and analysis of the combined shaft-corridor DSF ....................... 129
7.7 Conclusion .................................................................................................................... 131
Chapter 8.0 Parametric Optimization Studies of the Combined Shaft-corridor DSF ........... 134
8.1 Introduction .................................................................................................................. 134
8.2 Parameters examined.................................................................................................... 135
8.3 Parametric runs: Simulation results.............................................................................. 136
8.3.1 Impact of opening size on energy use and thermal comfort ................................. 138
8.3.2 Impact of cavity depth on airflow, energy use, and thermal comfort ................... 143
8.3.3 Impact of shaft height on energy use and thermal comfort .................................. 147
8.4 Double skin facade performance assessment ............................................................... 151
8.4.1 Comparison of the best comfort performance alternatives ................................... 151
8.4.2 Comparison of the best energy performance alternatives ..................................... 152
8.5 Comparison of the three optimum performance alternatives ....................................... 153
8.6 Optimization results and findings ................................................................................ 155
8.7 Summary and Conclusions ........................................................................................... 157
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8.7.1 Energy performance assessment ........................................................................... 158
8.7.2 Thermal comfort performance .............................................................................. 160
Chapter 9.0 Contribution and Future Works ........................................................................ 162
9.1 Contribution ................................................................................................................. 162
9.2 Limitation and recommendations for future work ....................................................... 163
9.3 Conclusion .................................................................................................................... 165
9.4 Final note ...................................................................................................................... 166
References ................................................................................................................................... 167
APPENDIX A: Drawings ........................................................................................................... 179
APPENDIX B: Weather data ...................................................................................................... 181
APPENDIX C: DesignBuilder‘s input -Shaft-corridor type facade ........................................... 189
APPENDIX D: PMV graphs of all 36 simulations ..................................................................... 193
APPENDIX E: Impact of parameters on cooling and heating energy ........................................ 198
viii
List of Figures
Figure 1.1 Statistical average energy consumption breakdown in U.S. office buildings ............... 4
Figure 2.1 Neutral pressure level for buoyancy-driven ventilation .............................................. 15
Figure 2.2 Wind-driven ventilation: Airflow direction and pressure versus height ..................... 17 Figure 2.3 Combined wind-buoyancy ventilation: Airflow direction and pressure versus height 19 Figure 2.4 Left: Buoyancy-induced airflow. Middle: Wind-induced airflow. Right: Combination
of both driving forces(Daniels, 1998) ........................................................................................... 20 Figure 2.5 Sketch of single-sided ventilation system ................................................................... 21
Figure 2.6 Sketch of stack ventilation........................................................................................... 22 Figure 2.7 The BRE building with chimneys extending well above roof level to increase the
stack potential and achieve stabile wind-induced suction ............................................................ 26
Figure 3.1 Typical DSF (Angus. 2001) ........................................................................................ 30 Figure 3.2 Heat transfer through a single pane of glass (Yellamraju, 2004) ................................ 33 Figure 3.3 Heat transfer through a DSF on a summer day (Haase, 2006) .................................... 33
Figure 3.4 The three main criteria for classifying DSFs (Hasse, 2006) ....................................... 34 Figure 3.5 The five ventilation modes: outdoor air curtain; indoor air curtain; air supply; air
exhaust, and air buffer................................................................................................................... 35 Figure 3.6 Box-window type: Plan (a); section (b); elevation(c) (Osterle, 2001) ........................ 37 Figure 3.7 William Farrell Building: (a) section showing DSF (b) northeast corner of building 38
Figure 3.8 Shaft box facade: Plan (a), section (b) and elevation(c) (Osterle, 2001) .................... 39
Figure 3.9 Shaft box facade: Plan (a), section (b) and elevation(c) (Osterle, 2001) .................... 39 Figure 3.10 CCBR south elevation (a) South facade section (b) west facade section .................. 40 Figure 3.11 CCBR cavity details .................................................................................................. 40
Figure 3.12 Corridor facade: plan (a); section (b) and elevation (c) (Osterle, 2001) ................... 42 Figure 3.13 Seattle Justice Center: (a) model of cavity section (b) model of building from south
....................................................................................................................................................... 42 Figure 3.14 Multistory DSF: Plan (a); section (b) and elevation(c) (Osterle, 2001) .................... 44
Figure 3.15 Occidental Chemical Building, southwest corner ..................................................... 44
Figure 4.1 Components of thermal comfort .................................................................................. 55 Figure 4.2 Relation between operative temperature and humidity ............................................... 56 Figure 4.3 Urban pressure distribution (Wolf Point Chicago and surroundings) ......................... 60 Figure 4.4 The effects of combined wind and stack forces: (a) reinforcing vs. counteracting effect
(b) depiction of counteracting wind and stack effect over a progression of wind speeds (Alloca et
al., 2003) ....................................................................................................................................... 61
Figure 4.5 The schematic diagram of the office module's inputs: 1)upper air outlet to chimney; 2)
interior upper operable window; 3) controllable solar control device; 4) interior operable or fixed
view window; 5) exterior glazing layer; 6) air cavity; 7) interior ................................................. 63 Figure 4.6 The air path inside the double skin facade transition from laminar to turbulent flow 67 Figure 4.7 The mesh generated for a combined shaft-corridor DSF in Gambit. .......................... 69
Figure 4.8 The CFD procedure of modeling to be converged ...................................................... 73 Figure 4.9 Convergence of residuals ............................................................................................ 75 Figure 4.10 Velocity vector profile in the combined shaft-corridor DSF office spaces ............... 76
ix
Figure 6.1 Energy components of typical office buildings (US Department of Energy, 2003) ... 87 Figure 6.2 Energy breakdown of a typical (right) and best-practice (left) building based on DOE
surveys .......................................................................................................................................... 88
Figure 6.3 Left: View of the building in the site Right: Site Plan (Source:
www.maps.google.com) ............................................................................................................... 89 Figure 6.4 Office Layout............................................................................................................... 90 Figure 6.5 View of the modled proportion of the single skin facade in DesignBuilder ............... 90 Figure 6.6 Fuel use break down of the reference building ........................................................... 95
Figure 6.7 Fuel breakdown of the simulated result with percentage of usage 274 total energy
intensity use .................................................................................................................................. 95 Figure 6.8 The reference building‘s heating and cooling consumption ........................................ 96
Figure 6.9 Diagram of the simulated double skin facades ............................................................ 97 Figure 6.10 Sketch plan of the new configuration ........................................................................ 98 Figure 6.11 The combined shaft-corridor DSF configuration and show air flows within the
building ......................................................................................................................................... 99 Figure 6.12 Energy breakdown in the combined shaft-corridor DSF configuration .................. 100
Figure 6.13 Annual gas and electricity demands ........................................................................ 101 Figure 6.14 Annual net cooling demand for each month............................................................ 102 Figure 6.15 Cooling energy demand for four different enclosures ............................................. 103
Figure 6.16 Heating energy demand for each month .................................................................. 104 Figure 6.17 Impact of facade types on energy use ...................................................................... 105
Figure 6.18 Energy intensity of alternatives ............................................................................... 105 Figure 6.19 Average mean temperatures for reference and alternatives .................................... 106
Figure 6.20 PMV differences in four enclosures ........................................................................ 107
Figure 7.1 Weather data for May 14th, 2009, Chicago, Il .......................................................... 110
Figure 7.2 Weather date for June 14th, 2009, Chicago, Il .......................................................... 110 Figure 7.3 Weather data for Sep 16th, 2009, Chicago, Il ........................................................... 111 Figure 7.4 Weather data for Oct 15th, 2009, Chicago, Il ............................................................ 111
Figure 7.5 Wind distribution around the office at ground level (yellow: high wind speed, green:
moderate wind speed, and blue: low wind speed). The date of the simulation is May 1st ......... 112
Figure 7.6 Velocity distribution around the building the prevailing wind, south at 5m/s .......... 115 Figure 7.7 Vertical cross section of the combined shaft-corridor DSF ...................................... 116
Figure 7.8 Three-dimensional grid model of the seven-story building with combined shaft-
corridor DSF configuration shown the gambit output ................................................................ 116 Figure 7.9 Model boundary settings ........................................................................................... 117
Figure 7.10 As displayed in Fluent analysis of room temperature profile.................................. 120 Figure 7.11 Cavity temperature gradient .................................................................................... 120 Figure 7.12 Cavity temperature profile-output from Fluent ....................................................... 121 Figure 7.13 Chimney air temperature profile ............................................................................. 122
Figure 7.14 The horizontal temperature profile of the room ...................................................... 122 Figure 7.15 Model of air velocity vector in the building ............................................................ 123 Figure 7.16 Horizontal velocity profiles ..................................................................................... 124 Figure 7.17 Horizontal velocity gradient .................................................................................... 124 Figure 7.18 Model of air velocity close to the inlet opening ...................................................... 125 Figure 7.19 Airflow patterns and velocity at the chimney‘s outlet opening ............................... 126
x
Figure 7.20 Air velocity vectors in the cavity and chimney ....................................................... 127 Figure 7.21 Velocity vectors in the chimney and cavity ............................................................ 128 Figure 7.22 Velocity vectors in the room ................................................................................... 128 Figure 7.23 Average PMV index first floor months under study ............................................... 130
Figure 7.24 Average PMV as calculated in the room ................................................................. 131
Figure 8.1 Parametric variables used in CFD. ............................................................................ 135 Figure 8.2 Impact of opening size on energy use ....................................................................... 139 Figure 8.3 Impact of opening size with shaft height (7-story), cavity depth (1.5 m) on comfort140 Figure 8.4 Impact of opening size with 9-story shaft height, 1.5 m cavity depth on comfort ... 141
Figure 8.5 Impact of opening size with 5-story shaft height, 1.5 m cavity depth on comfort .... 141 Figure 8.6 Airflow for different opening sizes (from right: 0.3m-0.6m-0.9m) .......................... 142 Figure 8.7 Impact of cavity depth on comfort with constant 7-story shaft height, 0.3m opening
size .............................................................................................................................................. 143 Figure 8.8 Impact of cavity depth on comfort with constant 9-story shaft height, 0.3 m opening
size .............................................................................................................................................. 144
Figure 8.9 Impact of cavity depth on comfort with constant 5-story shaft height, 0.3 m opening
size .............................................................................................................................................. 144
Figure 8.10 Impact of cavity depth on comfort with constant 7-story shaft height, 0.6 m opening
..................................................................................................................................................... 145 Figure 8.11 Impact of cavity depth on energy use ...................................................................... 147
Figure 8.12 Impact of shaft height on comfort with constant 1.5 m cavity depth, 0.3 m opening
size .............................................................................................................................................. 148
Figure 8.13 Impact of shaft height on comfort with constant 1.2 m cavity depth, 0.6 m opening
size .............................................................................................................................................. 148
Figure 8.14 Impact of shaft height on energy use with 1.5 m cavity depth and 0.3 m opening size
..................................................................................................................................................... 150
Figure 8.15 Impact of shaft height on energy use with 1.2 m cavity depth and 0.3 opening size
..................................................................................................................................................... 150 Figure 8.16 Monthly average PMV for the different alternatives .............................................. 151
Figure 8.17 Energy use comparisons for different alternatives .................................................. 153 Figure 8.18 Energy use of optimum alternatives ........................................................................ 154
Figure 8.19 PMV index of optimum alternatives ....................................................................... 154 Figure 8.20 Opening size vs. cavity depth .................................................................................. 156
Figure 8.21 Opening size vs. shaft height ................................................................................... 156 Figure 8.22 Cavity depth vs. shaft height ................................................................................... 157
xi
List of Tables and Graphs
Table 4.1 Thermal Environment Conditions for Human Occupancy from ANSI/AHRAE
Standard55-2004 ........................................................................................................................... 57
Table 4.2 Boundary condition sample .......................................................................................... 71
Table 6.1 Energy components of typical and best practice office building in Chicago ............... 87 Table 6.2 Occupants schedule and activity level .......................................................................... 91 Table 6.3 Description of building construction ............................................................................ 92 Table 6.4 Properties of window on south facade .......................................................................... 93
Table 6.5 Reference building simulation results, heating and cooling energy ............................. 96 Table 6.6 Energy intensity of 4 cases and the percentage of savings ......................................... 106
Table 6.7 Summary of results ..................................................................................................... 108
Table 7.1 Model assumptions and inputs required by Fluent ..................................................... 119 Table 7.2 The Fluent model information .................................................................................... 129 Table 7.3 Calculated air velocity in the office room: 0.5 meter from the windows and 1 meter
from the floor. ............................................................................................................................. 129 Table 7.4 Calculated air velocity in the office room: 0.5 meter from the windows and 1 meter
from the floor. ............................................................................................................................. 130
Table 8.1 Simulation results for different scenarios of the combined shaft-corridor DSF. ........ 138
Graph 8.1 Temperature comparisons for different opening sizes (Shaft height: 7-story) .......... 142
Graph 8.2 Temperature comparisons for different cavity depth and shaft height ...................... 146 Graph 8.3 Temperature comparisons for different cavity depth and shaft height ...................... 146
Graph 8.4 Temperature comparisons for different shaft height and cavity depth ...................... 149
1
Chapter 1.0
Introduction
With the emergence of energy-consumption reduction as a major national concern, the search for
better approaches in improving both thermal comfort conditions and the energy efficiency of
buildings is intensifying. Currently, low-energy building design features include lighting and
controls, ventilation systems, and an improved building envelope. Lighting energy can be
reduced through the use of natural daylighting, high efficiency fixtures and controls, such as
occupancy sensors that turn lights off when there is no movement, and photosensors that reduce
light output as needed to maintain a minimum level. These technologies, combined with
architectural details like light shelves, high windows, external shading, and double-skin facades,
increase natural daylight while reducing energy consumption associated with artificial light.
Energy-consuming systems required for providing fresh air to meet indoor air quality
requirements can be reduced or eliminated with the use of passive or hybrid technologies. Hybrid
ventilation, or the use of natural and mechanical systems to cool and ventilate buildings, offers
opportunities to take advantage of external conditions, but require a backup system to maintain
the indoor environment when these conditions are not adequate. Additionally, the building
facade plays an important role in achieving energy conservation. Due to technological advances,
transparency and the use of glass has become an attractive envelope option in architectural
design. Building glass facades can provide outdoor views and an excellent level of natural light
as well as the potential for natural ventilation. However, with the use of glass, heat loss during
the winter and solar gain during the summer will increase energy loads. In central Europe, which
has moderate-to-cold climates, new concepts were tested that used outdoor conditions in creating
climatic-responsive buildings (Givoni, 1998; Szokolay, 1980; Wigginton, 1996). Advanced
2
facade technologies were developed for the high-end office building sector, in particular
(Wigginton, 2002), and designers tried to integrate more building services into the facade
system. By integrating the use of thermal mass, building-envelope systems can help temper the
internal environment, and reduce the amount of supplementary heating or cooling needed to
maintain occupant comfort.
In addition to overall building performance, indoor environment conditions and occupant
comfort have emerged as important design considerations in both mechanically and naturally
ventilated buildings. Passively cooled and ventilated buildings have many benefits not only in
reduced energy consumption and reduced ventilation-equipment first costs, but also in terms of
occupant environment. Occupant comfort, though difficult to measure quantitatively, has been
evaluated through tools such as the PROBE studies. These surveys indicate that indoor
temperature associated with occupant thermal comfort has a larger range in naturally ventilated
buildings (de Dear and Brager ,2000) extending the range of exterior temperatures over which
natural ventilation is usable. Interior temperature is only one aspect of the indoor environment,
which also includes air velocity and surface temperatures. Although high air velocity has
prompted concern over paper disturbances in naturally ventilated building designs, slightly
higher velocities can help maintain comfort when higher internal temperatures are experienced.
With slight increases in velocities—0.1 m/s to 0.25 m/s—occupants can tolerate a temperature
increase of 3.6°C without any additional discomfort (Chandra et al., 1986). For air velocities
within the occupied space up to 0.4m/s, occupants can tolerate interior temperatures of 28°C or
30°C(with relative humidity range 50-80%) as long as there are cooler surface temperatures on
surrounding walls, floors, or ceilings (Allard, 2002 and Brager, 2004). Cooler surface
temperatures can be achieved through proper use of thermal mass in the building design.
3
Passively cooled and ventilated environments have increased occupant satisfaction when
occupants have the ability, or perceived ability, to control their own environment through the use
of operable windows (Jones and West 2001).
The location of the building affects performance as well. Climate influences the feasibility and
usage period of natural ventilation as a means of cooling. Buildings in temperate climates can
use natural ventilation for most of the cooling season, which is usually from May through
October. In climates with a wider temperature range, including hot summers, passive cooling is
still possible, but greater attention to detail and design must be made. US has been divided into
17 different climate regions based on maximum, minimum, average monthly temperatures,
humidity, wind, sunshine and degree days. Of the 17 climates identified, 12 regions could benefit
from natural ventilation, at least for a portion of the cooling period (Jones and West, 2001).
1.1 Building Energy Use
Energy use in the building sector accounts for a large proportion of total energy use in most
developed countries. In the U.S., buildings are responsible for half of all energy consumption,
while industry and transportation consume 27 percent and 29 percent, respectively. Because the
built environment consumes the largest amount of energy, developing building designs that
consume less operational energy during their lifecycle is critical. The breakdown of sub-system
energy usage in commercial office buildings in the U.S. is presented in Figure1.1. The majority
of energy is used in heating, cooling, and ventilating occupied spaces. The situation is even more
critical for office buildings, which consume the highest amount of energy across the building
spectrum, as shown in Figure1.1. A study done by EIA in 2005 showed that commercial
buildings consumed 21 percent of total U.S. energy. Although heating comprises most of the
4
country‘s energy usage, cooling is also a significant portion, representing almost 23 percent of
total building primary-energy use (EIA, 2005).
Figure 1.1 Statistical average energy consumption breakdown in U.S. office buildings
In office buildings, the use of natural ventilation techniques can be a potential design-strategy
component. Heating and cooling loads could be decreased by incorporating energy efficient
technologies, control schemes, and improved building-envelope design. Designers and engineers
can continue to improve the building envelope and facade treatments to reduce heat loss and
solar gains through the windows, thereby decreasing heating and cooling requirements and
minimizing differences between indoor air and surface temperatures that may cause occupants
discomfort. The increased use of thermal mass to temper indoor air temperature has become
more widely used in commercial building design. In hot summer continental climates like
Chicago, the energy consumption required to cool and ventilate a building can be reduced by
incorporating natural ventilation in the building design during the shoulder seasons, though it is
5
not often done. In most climates suitable for natural ventilation, there are only a handful of
buildings with this type of system.
Transparency and the use of glass has also become an attractive envelope option primarily in
high-rise buildings. The challenge is to improve building performance while providing a more
comfortable and healthier place for users. Fortunately, there are numerous methods and
techniques that can be employed to achieve these goals.
New enclosures that can substantially reduce energy usage by allowing natural ventilation is a
promising development. Aesthetics aside, a double-skin facade (DSF) is believed to reduce
cooling loads, allow for more or better natural ventilation, and provide natural ventilation in
high-rise buildings. The aim of this study is to propose an effective way to reduce energy
consumption in an office building during cold and hot seasons. Therefore, it will focus on how
DSF works in such climates. The primary goal of the dissertation is to clarify the state-of-the-art
performance of DSFs, so that designers can assess the value of these building concepts in
meeting design goals for energy efficiency, ventilation, productivity, and sustainability.
1.2 Problem statements and difficulties
Developing new facade technology is necessary for more environmental friendly and energy-
conscious building design. While a great deal of interest exists in learning how to integrate DSFs
into our current architecture, there is little knowledge or demonstration of how the concept might
work in a city such as Chicago. Studies on DSF energy performance have been mostly limited to
the colder and more temperate climates of central Europe. However, the use of DSFs in hot
summer continental climates is not well documented. In addition, numerous papers describe how
DSFs should improve a building‘s energy efficiency through principles and ideas yet provide no
calculated or experimental results (Lieb, 2001; Arons and Glicksman, 2001). Other researchers
6
have provided simulation models to specific DSF typologies, but have not linked the envelope-
results level to the building energy performance or do not couple the model to a building-energy
simulation program (Saelens, 2003). Most of the papers regarding a facade and energy-modeling
combination are restricted to only one DSF typology (Saelens, 2003). This study attempts to
analyze a new DSF configuration (a combination of two current typologies: corridor and shaft) in
a Chicago office building in terms of energy and thermal comfort. A base case with conventional
skin will be simulated. Then the building‘s performance will be simulated with the proposed new
DSF (combined corridor-shaft) configuration. A series of varied parameters will provide the
maximum thermal comfort. Final comparisons will be made between the proposed options and
the base case to find the most efficient strategy with maximum thermal comfort.
Although natural ventilation has the potential to significantly reduce energy consumption in
relation to cooling buildings, several factors impede its application in commercial office
buildings. There is concern over building performance and occupant comfort, particularly in
regards to warm temperatures outside occupants‘ comfort areas or other interior environmental
aspects. There is not only a lack of understanding of natural ventilation and the resulting
temperatures and airflows for specific climates, but also a lack of comprehensive tools to analyze
detailed design strategies effectively.
1.3 Goals of this Research
The use of either fully naturally ventilated, or partially, when mixed with mechanical ventilation,
has, so far, not been attempted in large office buildings in hot summer continental climates. This
type of ventilation is more preferable to a mechanically ventilated counterpart because of the
possibility of reducing high air-conditioning energy demands, and can also provide a
comfortable and healthy indoor environment.
7
In high-rise buildings, natural ventilation is not viable in the upper levels due to high wind
speeds. The main problem with applying natural ventilation to high-rise buildings arises from the
high pressure differences that can be generated by buoyancy, due to the large value of H in
equation ∆p = ∆Tρgh i.e. since the building acts as a single space, the overall height H is the
determinant of the buoyancy force. Taking H = 180 m and ∆T = 20 K the pressure difference
across the envelope at ground level could be up to 140 Pa. Such pressures could cause problems
in opening doors and windows (the force on a 1.5 𝑚2 opening would be 210 N) (Etheridge,
2008). However, double facades are built to allow natural ventilation in high-rise buildings,
which is a great benefit. The possibility of exploiting natural ventilation due to the complexity
of physical phenomena that is non-linearity or left to the chaotic behavior of air movement is not
characterized by one solution. Therefore, the major tool necessary for design analyses is
Computational Fluid Dynamics (CFD).1 CFD is used to study the airflow and temperature
distribution in occupied spaces and evaluates different combinations of window openings and
outside conditions.
In exploiting natural ventilation, the challenge is to design a window-opening system that
provides a good supply of air across a narrow-width, European-type floor plate without causing
draughts near openings. Even with building mock-ups and wind tunnel models can be time-
consuming and expensive, there is substantial risk of getting the design wrong. Using the type
and level of technology normally reserved for Formula One racing cars, CFD has the potential to
test numerous design modifications before construction begins.
The aim of this study is to investigate the performance of a new DSF configuration for an office
building in terms of thermal comfort and energy consumption in a climate that is both cold and
1 CFD codes numerically solve the differential equations, which govern fluid dynamics (Navier-Stokes equations). It is solving
for three-dimensional, fluid flow problems by solving conservation of heat, mass, momentum, and other transport equations using
control-volume technique.
8
humid. The significant lack of information describing the complexity and challenges of
designing large, naturally ventilated buildings with DSF as a means to save energy with better
thermal comfort is addressed in the literature review.
The following questions hope to be answered satisfactorily in this study:
a) Can we take the design strategies that performs well in central Europe to a new location and
climate, such as Chicago?
b) Is it possible to use DSF technology to achieve natural ventilation in a commercial building?
c) How well does DSF technology perform in high-rise buildings in hot summer continental
climates?
1.4 Scope of document
This thesis presents the foundation of a methodology for modeling natural ventilation airflow in
high-rise office buildings with a new DSF configuration (combined shaft-corridor). This thesis
also explores the viability of combined shaft-corridor DSF designs to provide natural ventilation
as an energy efficient solution by means of numerical simulations using CFD coupled with
dynamic energy-simulation tools. Actual measured data of the building‘s energy performance
based on a full-scale model is not in the scope of study. Therefore, the base case is essentially a
simulated base case and is not calibrated with an actual model.
- The simulated combined shaft-corridor strategy is compared with the simulated base case.
In addition, the issue of condensation of the facade system has not been taken into account.
As there is no exact method of local comfort measurements, the predicted-mean vote was used to
evaluate the comfort performance.
The organization of this thesis is as follows:
Chapter 2: Natural Ventilation Strategies.
9
This chapter presents the three types of natural ventilation and building characteristics
that are often considered in the design of naturally ventilated buildings. It also describes the
various natural ventilation strategies and their positive impact on reducing energy
consumption in high-rise office building design, and the use of DSF technologies in
achieving naturally ventilated buildings.
Chapter 3: Double Skin Facade and Natural Ventilation.
This chapter provides a detailed look at the research and findings of various aspects of
DSFs through a literature review. It illustrates the history, categories, functioning, and
applications of DSFs.
Chapter 4: Application of CFD in Built Environment.
This chapter describes the application of CFD in architecture. There is a short description
of the use of Gambit and Fluent to model buildings‘ airflow and how to simulate the
buoyancy and wind effects as driving forces.
Chapter 5: Methodology.
This chapter presents the modeling process of the high-rise with the combined shaft-
corridor configuration using CFD simulation (Fluent) coupled with a dynamic-building
energy simulation tool (EnergyPlus). The knowledge gap and goals for research will be
explained.
Chapter 6: Energy Performance Assessments.
This chapter describes the base case model through two facade types, and the newly
designed DSF type. It also assesses the energy and thermal comfort DSF performance in
comparison with a typical single-facade system.
Chapter 7: Air Flow Modeling of a combined shaft-corridor DSF Configuration
10
This chapter explains natural ventilation in the combined shaft-corridor DSF
configuration and demonstrates results of temperature and velocity profile through the
building.
Chapter 8: Parametric Studies of the combined shaft-corridor DSF configuration
This chapter studies the different parameters that enhance the combined shaft-corridor
DSF configuration‘s energy and thermal performance. The modeling and simulation are
employed to support the design process comprising an iterative process of performing
simulations based upon ambient boundary conditions. Also included are analyses and
comparisons of alternative design processes. A summary of the methods developed for
evaluating natural ventilation in high-rise buildings with DSF using an airflow analysis
coupled with energy simulation are also presented.
Chapter 9: Contributions and Future Work.
Regarding the complexity of analyzing DSFs, a few assumptions have been made and
limitations are acknowledged. In this chapter, contribution and limitations of the research are
discussed and the future work areas are also presented.
11
Chapter 2.0
Natural Ventilation Strategies
2.1 Introduction
Natural ventilation has been used as a healthy solution for ventilating and has the potential to
reduce energy costs required for air conditioning. The possibilities of incorporating natural
ventilation should be reconsidered, as the effort of the last half century have been almost solely
on optimizing mechanical rather than natural ventilation. The goal of modern natural ventilation
is to utilize natural driving forces as effectively as possible, for as long as possible, to minimize
the use of energy for cooling.
With the advent of more densely populated office buildings that have more computers, higher
internal heat loads, and deeper floor plans, there has been a shift toward tighter construction
which controls the air introduced into the building, usually cooled mechanically. Increased heat
loads and concerns over occupant comfort have often restricted the use of natural ventilation in
commercial office buildings, even in temperate climates. Achieving a uniform internal
temperature for occupant comfort was thought to be possible only by controlling the amount of
air being supplied to an occupied space and its temperature.
Summer conditions are usually the primary occupant-comfort concern. During that time, the goal
is to ventilate to meet comfort requirements and cool the space using purpose-provided openings.
A well-designed and naturally constructed ventilated building should be able to perform
satisfactorily year round. A focus of this research is on evaluating airflow patterns and velocities
that can be created by natural ventilation in a commercial office building during shoulder season.
12
This chapter provides an overview of ventilation strategies from the types of ventilation to
specific design elements. First the types of ventilation, buoyancy-driven and wind-driven, are
presented. Then DSF design characteristics in naturally ventilated high-rise buildings are
outlined, followed by a brief description of the reference building and its specific characteristics.
2.2 Natural ventilation mechanism: Driving forces
There are two main forces that drive natural ventilation: stack or buoyancy-driven ventilation
and wind-driven ventilation. The properties of these two are elaborated in the following section;
both individual and combined effects are described.
2.2.1 Stack pressure: Thermal buoyancy
Buoyancy-driven ventilation is prevalent in many naturally ventilated buildings, with air flow
caused by pressure differences across the building envelope. With this type of ventilation the
pressure differences are due to air density differences, which in turn are due to temperature
differences. It is the magnitude of these temperature and resulting pressure differences, as well
as the building-opening characteristics that determine the magnitude of the buoyancy airflow. In
stack-driven ventilation, height is increased and therefore the pressure difference between an
inlet and outlet is increased.
A neutral pressure level (NPL) is created at the point where internal pressure is equal to the
external pressure, resulting in no airflow in or out of an opening at that particular height. Above
or below the NPL, airflow and direction can be determined; it is always from the higher-pressure
region to the area of lower pressure. In other word, a temperature difference between the inlet
and outlet can enhance the effects of buoyancy-driven ventilation. When the inside air
temperature is greater than the outside air temperature, air enters through openings in the lower
13
part of the building and escapes through openings at a higher level. The flow direction is
reversed when the inside air temperature is lower than the outside temperature. Calculation of
stack pressure is based on the temperature difference between the two air masses and the vertical
spacing between the openings.
The NPL can be calculated based on the total inlet and outlet areas and respective resistances,
and their relative height if more than one floor level exists. Roof openings and chimneys or
raised stacks can shift the NPL, usually to higher levels. For buoyancy-driven flow, the NPL is
presented graphically in Figure 2.1.
The Bernoulli equation is used to derive the flow from buoyancy-driven ventilation, calculating
the pressure differential due to height—i.e., the hydrostatic head, for both the exterior and the
interior environment. The overall pressure difference between the interior and exterior can be
expressed in terms of the height difference, H, gravitational constant, g, density at a reference
temperature, ρo, and the interior and exterior temperatures. The Bernoulli equation is given as:
constantgzρ
PvO
OO 2
2
(2.1)
For the buoyancy-driven case, there is no external velocity so the relationship reduces to:
constantgzP
O
O
O
(2.2)
The pressure difference is applied to the outside environment, using subscript E, and the internal
environment, using subscript I. The resulting pressure differences due to height between an
origin height, zO, and at some height H, zH, for the outside and inside become:
OHEE zzgP (2.3)
OHII zzgP (2.4)
14
To determine the total pressure difference, ΔPT, the difference across the inlet and outlet
openings is calculated. Figure 2.1 illustrates this, with it resulting in:
IOIOHOHI gHPPPP 0,0,,, (2.5)
It is assumed that air is a perfect gas, so the ideal gas law is used:
RT
P (2.6)
and substituted into equation 2.5 for the ρO and ρI terms. Since the difference between PO and PI
is negligible compared to atmospheric pressure, the term P/RTB is moved outside of the
parenthesis, and the ideal gas law is again applied. Equation 2.5 to describe the pressure
difference due to buoyancy-driven flow then becomes:
I
OI
OTT
TTgHP (2.7)
The Boussinesq approximation is used for ideal gases, so that β=1/TI. The density differences
are assumed to be negligible in the Boussinesq approximation except to determine ΔPT, since the
density of air does not vary significantly with temperature over the range of temperature
differences found in the reference building. The value for β used is the inverse of an average
internal temperature. The Boussinesq approximation is generally valid as long as ΔT<30°C
(Etheridge, 1996).
The ventilation rate is calculated by using the square root law (Etheridge, 1996), and the
Boussinesq approximation, and substituting in equation 2.7 to yield:
OId
I
OIdd THTgAc
T
TTgHAc
PAcQ
**2 (2.8)
15
Where Q is the flow rate through a building or space, Cd is the coefficient of discharge, and A* is
the contribution of inlet and outlet areas. A* is defined by:
2
2
2
1
2
2
2
1*
AA
AAA
(2.9)
Figure 2.1 Neutral pressure level for buoyancy-driven ventilation
When natural ventilation is used in a buoyancy-driven case, the airflow is not assisted by forced
air from wind or mechanical systems. This is often considered a critical design situation during
warm summer months for applying this passive technique in buildings. In a buoyancy-driven
case, the following parameters are somewhat interdependent, making the analysis of this
ventilation scheme more complicated. The parameters include:
Size of inlets and outlets
Height of the space
Strength of the heat sources driving the airflow
Resulting temperature difference between the interior and exterior spaces due to the
interior heat source(s).
16
Additionally, complex building geometries, such as multiple floors that are directly or indirectly
connected, increase the difficulty of evaluating the forces that drive natural ventilation flow. It is
in part this complexity, combined with a lack of understanding of the physical mechanisms
involved in both buoyancy- and wind-driven natural ventilation that reduces the effective use of
natural ventilation in building design.
2.2.2 Wind-driven ventilation
Natural ventilation is influenced by several environmental conditions, the most unpredictable
being wind velocity—its speed and direction. Both of these factors are difficult to control and
analyze, especially in a full-scale building. In the actual environment, instantaneous wind speed
varies with time, and the pressure difference varies with building geometry and location on the
building surface. In most wind-driven natural ventilation experiments, a constant, uniform wind
speed is used. These design-wind speeds are often the mean wind speeds for a given location
over a specific period of time, often years or decades (Awbi, 2003).
Several equations have been developed to describe pressure differences due to wind-driven flow.
The equations below describe a case with a constant wind speed where wind pressure does not
fluctuate with time. However, for single-sided ventilation, fluctuations in wind speed may be
important. A diagram portraying wind-driven ventilation, airflow direction, and resulting
pressure versus height is presented in Figure 2.2. If the openings on opposite sides are identical,
pressure differences across the openings are equal to half the pressure difference across the
building when it is assumed there is negligible-pressure differential through the building‘s
interior. The Bernoulli equation, applied between a point at some distance from the face of the
building containing the window and the facade, then reduces to the ideal equation:
17
2
2
OOOw
UPP (2.10)
where Pw is the pressure due to wind at the facade and PO is the pressure away from the building,
and UO is a reference velocity away from the building. Any height differential for flow along a
particular streamline is neglected, so both gz terms are zero, and the velocity at the face of the
building is zero as it is the stagnation point. A pressure coefficient, cp, is used in the actual case,
and is a function of wind direction and measurement location on the building facade. The
resulting equations are:
2
2
OOPOw
UCPP (2.11)
2
POd
CAUCQ
(2.12)
where Q is the flow entering or leaving through the openings. The value of cp depends on the
geometry of the building and the location on the facade, and values are often obtained through
the use of wind tunnel experiments (Orme, 1999). The pressure on the exterior of the building in
Figure 2.2 is assumed to not vary significantly with height.
Figure 2.2 Wind-driven ventilation: Airflow direction and pressure versus height
18
2.2.3 Thermal buoyancy and wind in combination
Combined wind-buoyancy flow is more readily found in full-scale buildings, and these two
natural ventilation types can work together or in opposition. Figure 2.3 presents the airflow
direction and relation of pressure versus height in a combined buoyancy-wind natural ventilation
case. The total case pressures are added together to determine an opening:
BWT PPP
. (2.13)
Using the square root law presented in equation 2.8, the total flow rate through an opening is
calculated by:
TDT
PACQ
2 (2.14)
Substituting the pressure differences for each case into equation 2.12, and then the total pressure
difference into equation 2.13, the total flow rate, QT, becomes:
OBO
PDT TTHgU
CACQ 2
2
(2.15)
2
122
BQ
WQ
TQ (2.16)
where Qw is the flow rate component due to wind and QB is the component due to stack, or
buoyancy flow (Awbi, 2003).
19
Figure 2.3 Combined wind-buoyancy ventilation: Airflow direction and pressure versus height
There are concerns with the accuracy of this equation (Etheridge, 1996) in part due to the relative
effects of wind and buoyancy. When the buoyancy and wind effects were approximately equal,
the error in using equation 2.15 was usually 50 percent (Etheridge, 1996). The magnitude of the
errors associated with equation 2.15 depends on the distribution of both inlet and outlet openings
and the flow characteristics of those openings. At present, however, there are not many
simplified methods available for calculating the ventilation rate when wind and buoyancy are
simultaneously active.
Air change is driven in part by thermal conditions, so it is important to include a ventilation
component in the energy balance of a space. In a simple room, the total airflow, ρcPQTΔT,
added to the heat conduction through the building envelope must equal the interior-heat loads
under steady state conditions. The material properties, surface areas, and temperature difference
between the interior and exterior environment are used to calculate the conduction through the
walls and windows, Qwalls+windows=UAΔT. The internal loads, Qloads, typically include heat
due to occupants, equipment and lights. For steady state conditions, the energy balance equation
is:
OIPOIloads TTcTTUAQ (2.17)
20
Figure 2.4 Left: Buoyancy-induced airflow. Middle: Wind-induced airflow. Right: Combination of both
driving forces(Daniels, 1998)
The schematic drawing (left) shows buoyancy-induced pressure distribution upon the envelope
of a high-rise building with an oval shape. The inward-pointing dotted lines indicate under
pressure, and the outward-pointing solid lines indicate over pressure. Because of the interior and
exterior temperature differences, a pressure differential over the building envelope is created.
The schematic drawing (middle) shows the wind-induced pressure distribution upon the same
high-rise building. The inward-pointing dotted lines indicate the positive pressure created on the
windward side of the building envelope, and the outward-pointing solid lines indicate the under
pressure created on the building envelope on the leeward side. Both the positive and negative
pressure increase towards the top of the building as a result of the wind profile. The schematic
drawing (right) illustrates the combined effect of wind and buoyancy, and the distribution of
pressure differentials on the building envelope. The Figure 2.4 illustrates that pressure gradients
derived from buoyancy and wind forces can be summed. They either strengthen or neutralize
each other (Daniels, 1998).
21
2.3 Natural ventilation principles
The shape of a building together with the location of the ventilation openings dictates the natural
ventilation‘s manner of operation. One usually differentiates between three different ventilation
principles for natural ventilation:
Single-sided ventilation
Cross ventilation
Stack ventilation
The ventilation principle indicates how the exterior and interior airflows are linked, therefore,
how the natural driving forces are utilized to ventilate a building. The principle also indicates
how air is introduced into the building, and how it is exhausted. Infiltration through the building
envelope can also play a role, depending on how airtight it is. This form of ventilation is,
however, usually both unintended and unwanted.
2.3.1 Single-sided ventilation
Single-sided ventilation relies on opening(s) on only one side of the ventilated enclosure. Fresh
air enters the room through the same side as used air is exhausted. Rooms within a cellular
building with openable windows on one side and closed internal doors on the other side is an
example of this type of ventilation.
Figure 2.5 Sketch of single-sided ventilation system
22
As a rule of thumb, single-sided ventilation is effective to a depth of about 2–2.5 times floor-to-
ceiling height (CIBSE Application Manual AM10, 1997). With a single ventilation opening in a
room, the main driving force in summer is wind turbulence. In cases where ventilation openings
are provided at different heights within the facade, the ventilation rate can be enhanced by the
buoyancy effect. The contribution from thermal buoyancy depends on the temperature difference
between the inside and the outside, the vertical distance between the openings, and where the
openings are located. The greater vertical distance between the openings and the greater
temperature difference between the inside and the outside, the stronger the effect of the
buoyancy. Compared with other strategies, lower ventilation rates are generated, and air does not
penetrate far into the space.
2.3.2 Stack ventilation
Stack ventilation occurs when driving forces promote an outflow from the building, thereby
drawing in fresh air through lower-level ventilation openings. Fresh air typically enters through
lower-level openings, while used and contaminated air is exhausted through higher-level
openings (a reverse flow can occur during certain conditions). Designing the outlet to be in a
wind-induced underpressure region can enhance the effectiveness of stack ventilation.
Figure 2.6 Sketch of stack ventilation
As a rule of thumb, stack ventilation is effective across a width of 5 times floor-to-ceiling height
from the inlet to where the air is exhausted.
23
A typical example is a building with an elevated central area, in which warm and contaminated
air from the surrounding spaces rises to be exhausted through rooftop wind towers.
Due to its physical nature, the stack effect requires a certain height between the inlet and the
outlet. This can be achieved by a variety of methods, including increasing the floor-to-ceiling
height, tilting the profile of the roof, or applying a chimney or atrium. Stack ventilation also
resembles cross ventilation as far as some individual spaces are concerned, in that air enters one
side of the space and leaves from the opposite side. The air may flow across the whole width of
the building or from the building‘s edges to its middle to be exhausted via a central chimney or
atrium.
2.4 Elements of Natural Ventilation
Characteristic elements are utilized to enhance natural ventilation principles. These elements
distinguish natural ventilation concepts from other ventilation concepts and have consequences
with regard to architecture, economy, and performance.
However, natural ventilation can be realized without the use of dedicated elements. The building
itself can double as a ventilation element, which might be named, ―building integrated element‖.
In this case, the building is designed to harness natural driving forces and direct ventilation air
through its spaces without the need for specific ventilation elements. In this sense, a building‘s
integrated-ventilation element is really not an element, but rather an absence of one. As the
ventilation system and occupants share the same spaces (rooms, corridors, stairwells, etc.), and
windows and doors are utilized as part of the air paths, the most characteristic feature of this type
of system is the appearance of no system at all. There are no traditional natural ventilation
elements, nor mechanical ones. The main advantage of a building integrated-element system is
that it represents no additional use of building space. Most naturally ventilated buildings do,
24
however, make use of dedicated ventilation elements to harness natural driving forces and to
support airflow through the building. The elements used in this research are described in the
following section. A description of the advantages and drawbacks of the individual element
system is included.
2.4.1 Double facades
A double facade system involves the addition of a second glazed envelope, which can create
opportunities for maximizing daylight and improving energy performance. A double facade thus
has many properties in common with an atrium. However, the cavity in a double facade does not
offer space for occupation.
A natural ventilation double facade can be used as an outlet or inlet path in any of the three
natural-ventilation principles. They offer many important advantages such as:
The cavity is protected against wind and outdoor noise. Thus, open windows can be
utilized irrespective of wind and noise from the outside, even on the upper floors of high-
rise buildings.
Solar shading devices are protected from wind when placed in the cavity.
Solar preheating of the supply air is provided on sunny days, when the cavity is used as
an air supply path.
Due to the protected environment in the cavity, transmission losses through the wall are
reduced compared with an ordinary external wall. When used as a supply air path, some
of the transmission heat losses through the wall will be captured by the inlet airflow in
the cavity, thus providing a heat recovery effect.
Due to the protected climate in the cavity, inside window surfaces will be warmer,
reducing cold downdrafts and asymmetric radiation.
25
Drawbacks:
High cavity temperatures can be a problem on hot days, if the external glazing is not
operable. This is particularly a problem in the upper floors of a building, when the double
facade is used as an exhaust stack.
Noise can be transferred between adjacent rooms by reflection in the glazed cavity
surfaces.
Cleaning of the cavity is important, especially when used as a supply air path. This
implies higher operation costs than a normal facade.
A double facade represents significantly higher construction costs than a normal facade;
however, because they are usually not built solely for ventilation purposes, the costs can
be distributed for other functions, e.g., daylight and visual amenity.
2.4.2 Chimneys
Cylindrical-shaped chimneys are another common type of roof element in natural ventilation
systems. Most chimneys extract the ventilation air while providing an increased buoyancy effect.
Due to where chimneys are usually located—well above a building‘s roof—the opening is
conducive to strong, more stable winds thus increasing the potential to function as a driving force
for ventilation. Careful attention should be paid when designing the chimneys opening section to
maximize a building‘s underpressure. The simplest design is an open top, which ensures negative
pressure and provides suction in all wind directions due to the Bernoulli effect. To avoid ingress
of rain, a cover can be placed above the top. Alternatively, a combination design with roof cowls
might provide a greater degree of protection from the weather and increase the chimney‘s effect.
26
Figure 2.7 The BRE building with chimneys extending well above roof level to increase the stack
potential and achieve stabile wind-induced suction
An advantage of chimneys is that they offer an uncomplicated and efficient way of taking
advantage of both thermal buoyancy and wind, independent of wind direction.
2.5 Natural ventilation and high-rise buildings
Buildings are considered high rise when they are taller than ten stories. Several low energy
concepts can be incorporated into a high-rise building, including natural ventilation. The high
rise is therefore of particular interest and constitutes the focal point of this research.
Facades are the most important element of the low energy concept. A high degree of
transparency allows for maximum daylight and exterior views. Heat and light interior
transmission is controlled through the use of solar shutters and blinds; the double facade-buffer
zone contributes to good insulation values. The biggest factor to take into consideration when
deciding upon a high-rise ventilation is that the building‘s velocity profile increases with height.
The conventional way to solve this issue has been to seal the facade and put a mechanical-
ventilation plant into it. Due to the building‘s height, windows cannot be open and there is no
shading because it flaps around in the wind. Being in the middle of a city presents other issues
27
such as traffic, noise and air pollution. Therefore our concept was to close the facade with the
second skin and ventilate the offices into the double facade.
A number of interesting investigations and findings are reported in the literature pertaining to
passive ventilation in buildings with double-skin facades.
It was found that significant energy savings are possible if natural ventilation could be exploited
through the use of a double-skin facade (DSF). For example, the Loyola University Information
Commons and Digital Library in Chicago integrated natural ventilation with a DSF to cool the
buildings. The results indicated that an integrated facade can reduce 30 percent of energy
consumption (52 days operated in natural mode) (Frisch, 2005).
Even though most of the research has been done in temperate climate conditions, studies have
revealed a close link between natural ventilation design and the DSF function. Grabe et al.
(2002) developed a simulation algorithm to investigate the temperature behavior and flow
characteristics of natural-convection DSFs through solar radiation. It was found that the air
temperature increased near heat sources that are close to window panes and shading device.
Gratia and Herde (2004a, 2004b, 2004c, 2004d, 2004e, 2007a, 2007b, 2007c, 2007d) attempted
to look at natural ventilation strategies, greenhouse effects, and the optimum position of sun-
shading devices for DSFs facing south in a northern hemisphere temperate climatic. They found
that a sufficient day or night ventilation rate can be reached by a window opening, even if wind
characteristics are unfavourable. They also argue that with a south- facing DSF, there is a danger
when using the cavity air to ventilate the building during the cooling season when air flows
downward due to higher wind pressure at the upper openings. In this situation, air that has been
warmed in the cavity is drawn into the building and adds to the cooling load. During daytime
hours when there is incident isolation, the cavity air temperature is always higher than that of the
28
outdoor air. This suggests that a sophisticated louver control system is necessary to ensure that
cooling loads are not increased with natural ventilation in the case of a south-facing DSF. Care
must be taken to prevent greater wind pressure at the top cavity opening than at the bottom. On a
windward facade, airflow within the cavity is almost always determined by wind pressure rather
than buoyancy; therefore air flows downward, without a careful design to prevent it. This
phenomenon might lead to a northern-orientation DSF, if ventilation from operable windows is
the main goal. The authors further provided some general guidelines in improving natural
daytime ventilation in office buildings with a DSF and demonstrated that efficient natural cross
ventilation is possible in temperate climatic conditions.
2.6 Conclusion
Buoyancy and wind velocity are the two driving forces by which the outdoor fresh air can be
brought into an interior space and unwanted radiant heat (solar radiation and internal heat gains)
can be expelled externally. These principles are understood but more research needs to be done
to explore the full extent of DSFs‘ capabilities in reducing energy usage. In particular, there is a
great possibility for a shaft type facade system that reduces energy usage in high-rise buildings
through the use of natural ventilation strategies.
29
Chapter 3.0
Double Skin Facade and Natural Ventilation
3.1 Introduction
In the previous chapter the possibilities and issues of incorporating natural ventilation in
different facade system and high rise building presented. The main purpose of this chapter is to
provide an overview of various theoretical backgrounds regarding different aspects of building
facade systems (building science and aesthetic) and their impact on building performance. First,
a general definition of double skin facade system is presented. Then a brief history, which
describes the facade‘s evolution from early concepts to the present, is highlighted. The next
section explains different DSF typologies and classifications in terms of airflow driving force,
facade divisions, and the airflow modes, as well as the presentation of previous work. The final
section gives an overview of thermal performance considerations and envelope performances
during summer and winter seasons.
3.2 Definition Single Skin Vs Double
Single skin facade in typical buildings consists of different functional layers including cladding,
structure, insulation, etc which separates building interior from exterior. The emergence of
curtain walls in the nineteenth century which did not have a load bearing function, made it
possible to from an envelope made entirely of glass. Nevertheless, the issues related to thermal
comfort condition and low thermal performance of those lightweight single skin envelope
supported by the invent of mechanical system. The energy crisis of 1973 necessitates the
designer to exploit renewable energy sources for cooling, heating, lighting and ventilating a
building. Those issues resulted in developing new products in the glass industry to protect
30
unwanted heat gain in summer and optimize the use of daylight. Examples of such products
include glasses with different coatings. At the moment the architects tried to incorporate the use
of natural ventilation and solar energy which resulted in emergence of new concepts in the
facade system such as double skin facade.
A double skin facade (DSF) consists of a multilayered facade, which has an external and internal
layer that contains a buffer space used for controlled ventilation and solar protection (Arons,
2001). The use of multilayered skins uses building insulation against thermal variation and
external noise. As illustrated in Figure 3.1, a DSF could provide outdoor air through operable
windows, and preheat or precool the air introduced to the interior space by HVAC system. It can
integrate the mechanical ventilation with natural ventilation during the mild seasons.
Psychologically speaking, it can reconnect inhabitants with the outdoor and provide a healthy
environment while using a substantially smaller mechanical system.
Figure 3.1 Typical DSF (Angus. 2001)
31
3.3 History and background
The concept of DSF dates back to when many central European houses utilized box-type
windows to increase thermal insulation (Oesterle, 2000). In 1849, Jean-Baptiste Jobard, at that
time director of the Industrial Museum in Brussels, described an early version of a mechanically
ventilated multiple skin facade. He mentioned that in winter, hot air could be circulated between
two glazings; while in summer, cold air could be used (Saelens, 2002). Crespo and Neubert
mentioned that a doubleskin curtain wall appeared first in 1903, in the Steiff Factory in Giengen,
Germany, where priorities were to maximize daylight while taking into account the cold weather
and strong winds of the region. A DSF was assumed to be energy efficient and environmental
friendly, providing a 40-60 percent reduction in energy consumption, external noise reduction,
and natural ventilation even in skyscrapers (Oesterle et al., 2001). Aside from an aesthetic
viewpoint, such concepts are often chosen—particularly in high-rise buildings—for shading-
device protection from high wind pressure and the possibility of natural ventilation due to lower
pressure in the facade cavity.
3.4 Overview of the system
3.4.1 Thermal performance
This section discusses how DSFs perform in two different climate scenarios (winter and
summer):
1) During the winter, the external additional skin provides improved insulation by increasing
external heat-transfer resistance. Although the equivalent thermal transmission coefficient U-
Value for a permanently ventilated facade will be poorer in part (than with a single skin facade),
the results will improve if the intermediate space (cavity) is closed (partially or completely)
during the heating period. The reduced air-flow speed and increased temperature inside the
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cavity lowers the heat transfer rate on the surface of the glass which leads to a reduction of heat
loss. This has the effect of maintaining higher temperatures on the inside part of the interior
pane. Oesterle et al. (2001) describe the proportion of the opening area in order to improve
thermal insulation.
2) During the summer, once radiation passes into the building, it is absorbed by the building
fabric and re-radiated as long-wave infrared energy that does not pass back through the glass. As
a result, the air in the cavity will be heated via convection. The hot air flow in the cavity can pass
through the glazing outside and inside the space via conduction. As the cavity warms up the
stack effect is improved respectively. Figure 3.3 shows the effect of various factors on heat
transfer through the building‘s envelope and illustrates the impact of solar radiation, conduction,
and convection on the airflow through the DSF cavity. A DSF system results in less heat
transferred from outside to inside, and less energy required to cool the space. The rate of heat
transfer under steady-state conditions is known as the U-value (coefficient of thermal
transmission). The U-value expresses the heat flux (in W/ 𝑚2𝐾) through a building component
(or a combination of components) with a temperature difference of one degree across several
components under steady-state conditions. Figure 3.2 shows the heat transfer mechanism through
single pane glass; the heat transfer mechanism through DSF is illustrated in Figure 3.3. A low U-
value indicates that the building component has a high thermal resistance and can be expressed
in a case for a multiple-glassing unit by the following equation (Osterle, 2001):
𝑈 =1
1𝑒
+1𝑖
+1𝑡
Where: U= W/𝑚2𝐾 𝑒= External heat transfer coefficient (W/𝑚2𝐾)
𝑖= Internal heat transfer coefficient (W/𝑚2𝐾)
𝑡= Conduction of multiple glazing units (W/𝑚2𝐾)
(3.1)
33
Figure 3.2 Heat transfer through a single pane of glass (Yellamraju, 2004)
The exterior heat source is solar radiation, which is initially reflected on the external glazed skin
in this process and, depending on external conditions, determines the external heat transfer
coefficient 𝑒 . The remaining radiation passes through the glass. The reflection with the inner
glass and inner walls of the cavity creates processes of convection and conduction, which
determine the heat transfer coefficient inside the cavity𝑖 . The accumulated and remaining heat
by radiation and conduction received by the room determines the heat transfer coefficient 𝑡 .
Figure 3.3 Heat transfer through a DSF on a summer day (Haase, 2006)
𝑒 𝑖
INDOOR OUTDOOR
Conduction
Radiation
Reflection
Convection
Radiation
Convection
CAVITY
34
Three characteristics identify types of double skin facades. These are based on geometric
characteristics and also the ventilation mode and type.
As presented in Figure 3.4 these criteria are:
1. Type of ventilation
2. Partitioning of the facade
3. The modes of cavity ventilation
Figure 3.4 The three main criteria for classifying DSFs (Hasse, 2006)
3.4.2 Type of cavity ventilation
The two main driving forces of natural ventilation are the differences between the pressure
created by the stack effect and wind effects. Natural ventilation drives the air through a space by
taking advantage of the pressure differences caused by these two factors due to internal
temperature differences or a combination of both. Hybrid ventilation is a controlled compromise
between natural and mechanical ventilation. In hybrid ventilation, natural ventilation is generally
used; mechanical ventilation is only triggered when the driving forces of natural ventilation
become inadequate and make it no longer possible to achieve the desired performances.
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―Note: The stack effect (or chimney effect) is a phenomenon related to the rising of hot air.
Applied to a DSF, the concept of stack effect expresses the fact that air is lighter than cold air.
As the cavity is generally hotter than the outside, air has a tendency to escape at the top
(Loncour, 2002).
Figure 3.5 The five ventilation modes: outdoor air curtain; indoor air curtain; air supply; air exhaust,
and air buffer
3.4.3 Airflow concept
Based on the ventilation mode, the DSF was categorized into five groups. The ventilation mode
is independent of the type applied (the first classification presented). Not all facades are capable
of adopting all the ventilation modes described here; a facade is characterized by a single
ventilation mode. However, a facade can adopt several ventilation modes at different moments,
depending on whether or not certain components integrated into the facade permit it (i.e.
operable openings). One must distinguish between the following five main ventilation modes:
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Outdoor air curtain
In this ventilation mode, outside air introduced into the cavity is immediately turned back
outside. The cavity ventilation thereby forms an air curtain enveloping the outside facade.
Indoor air curtain
The air comes from the inside of the room and is returned to the same place or via the ventilation
system. The cavity ventilation forms an air curtain enveloping the indoor facade.
Air supply
The ventilation of the facade is created with outdoor air. The air then travels to the interior room
or into the ventilation system. This makes it possible to supply the building with air.
Air exhaust
Air inside the room is evacuated towards the outside. The ventilation of the facade thus makes it
possible to evacuate air from the building.
Buffer zone
This ventilation mode is distinctive as each of the double facade skins is made airtight. The
cavity thus forms a buffer between the inside and the outside, with no possible cavity ventilation.
3.4.4 Partitioning of the facade
Based on the geometry of the facade (width openings, cavity height and width, etc.), Oesterle et
al.(2001) categorized DSF into the following groups: box window, shaft window, corridor facade
and multi-story.
If the DSF extends over the entire height and width of the building, the term, facade, is
appropriate. If the facade is divided into smaller units, three main categories can be defined. If
the partitioning consists of vertical ducts, the expression shaft facade is adopted. When the
facade is horizontally partitioned, the term corridor facade is usually employed. If the facade is
37
both horizontally and vertically subdivided, the DSF is called window or box. The term windows
can be used for systems in which the windows act as DSFs. The term box is more appropriate for
entirely transparent envelopes with horizontal as well as vertical partitioning.
3.4.4.1 Box window
In this type, the facade is horizontally and vertically subdivided, with entirely transparent
envelopes. Horizontal and vertical partitioning divides the facade into smaller and independent
boxes. A box window is the oldest form of a DSF, and consists of a frame and inward-opening
casements. The cavity between two facade layers is divided horizontally and vertically along
constructional axes and floors, respectively. This type of window is common in areas with high
external sound levels and special requirements relating to sound insulation between adjoining
rooms. This form is the only type that provides the function of a DSF with a conventional way of
opening (Osterle, 2001).
(a) (b) (c)
Figure 3.6 Box-window type: Plan (a); section (b); elevation(c) (Osterle, 2001)
The Telus Headquarters (William Farrell Building)
Location: Vancouver, British Columbia, Canada
Building size: 130,000 𝑓𝑡2 , 7 stories
Architect: Busby + Associates Architects Ltd.
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Figure 3.7 William Farrell Building: (a) section showing DSF (b) northeast corner of building
This project was a renovation of an existing brick-face building in which the south and east
orientations were covered with a second glazed facade. The second facade provided a buffer
between the building interior and a busy Vancouver street, and the system allows for natural
ventilation through manually operable windows, the interior facade, and mechanically controlled
exterior windows. Occupants can control the exterior windows with switches at each floor.
Providing daylight access was also a driving force behind this new facade design, and light
shelves within the cavity and space helped to achieve this. In the heating season, the cavity
functions similar to a Trombe wall, with the masonry-interior facade storing heat from absorbed
solar radiation and transferring it to the building‘s interior space. Details of the cavity and
adjoining space are shown in Figure 3.13. Information about the cavity‘s performance was not
available.
3.4.4.2 Shaft type
In this case, a set of box-window elements are placed in the facade with continuous vertical
shafts that go along a number of stories to create a stack effect. On every story, the vertical shafts
are linked with the adjoining box windows by an opening. The stack effect draws the air from the
box window into the vertical shafts. The air also can be sucked out mechanically. This type of
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DSF is suited for low-rise buildings, since the height of stacks is limited (Osterle, 2001). Figure
3.7 shows the plan, elevation, section, and diagram of ventilation in the shaft type. The arrows
indicate the route of the airstream through the box windows and the common shaft.
(a) (b) (c)
Figure 3.8 Shaft box facade: Plan (a), section (b) and elevation(c) (Osterle, 2001)
Figure 3.9 Shaft box facade: Plan (a), section (b) and elevation(c) (Osterle, 2001)
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Center for Cellular and Biomedical Research
Location: Toronto, Canada
Architect: Behnisch, Behnisch & Partner
Figure 3.10 CCBR south elevation (a) South facade section (b) west facade section
Figure 3.11 CCBR cavity details
The proposed design for this building has a DSF on the south facade, adjacent to office spaces,
as well as on the west facade. The design intentions of both facades include: providing natural
ventilation while shielding from the elements, providing building security, reducing heat loss in
the heating season, increasing indoor comfort by tempering the interior wall temperature,
41
buffering sound pollution, providing an additional space that can be occupied, and allowing for
sufficient daylight access and control system.
As shown in Figure 3.16, the 3-feet wide cavity is large enough to serve as an occupied space.
Along the north facade, this space is an addition to the office workspaces, while on the west
facade, the cavity acts as an extension to the corridor. In both cases, the designers took advantage
of the cavity for the placement of shading devices, which are located both within the cavity and
in the office space for easy adjustment. Airflow through the cavity is driven only by natural
forces; catwalks at each floor allow air flow and provide shading. Occupants are able to
manually control the windows on the interior facade as well as cavity vents.
Given that 75 percent of the building‘s occupants will use natural ventilation when the ambient
temperature is above 15° C in the heating season and below 15° C in the cooling season, the
engineers predicted that savings would be 58 percent of annual energy costs over a conventional
facade.
3.4.4.3 Corridor type
When necessary, divisions occur horizontally along the corridor for fire protection or ventilation
reasons. The intake and extract openings are situated near the floor and the ceiling. They are
usually staggered to prevent extracted air on the floor from entering the space on the floor
immediately above (Osterle, 2001).
A plan, section, and elevation of a corridor facade are illustrated in Figure 3.9. As shown, the
intermediate space is not divided at regular intervals along its horizontal length and air flows
diagonally to prevent extracted air from the lower story being sucked in with the air supply of the
above floor. The section of corridor facade shows the separate circulation for each story.
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(a) (b) (c)
Figure 3.12 Corridor facade: plan (a); section (b) and elevation (c) (Osterle, 2001)
Example of Corridor type in the US : Seattle Justice Center
Location: Seattle, WA.
Building size: 310,500 𝑓𝑡2,12 stories
Building description: Police headquarters and municipal courts
Construction date: 2002
Architect: NBBJ Architects
Facade Engineer: Arup Consulting Engineers
Figure 3.13 Seattle Justice Center: (a) model of cavity section (b) model of building from south
This project had sustainable-design proponents behind it from the beginning; the mayor of
Seattle, Paul Schell, is a former dean of architecture at the University of Washington. In addition,
there was an architect on the city council who approved the project. Seattle had a goal of
achieving LEED silver ratings for all city-owned buildings, and wanted to make sustainable
aspects evident to both users and the general public.
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The DSF covers the southwest facade of the building and it was designed to allow for maximum-
daylight penetration while minimizing heat gain. The 30-in deep cavity is ventilated with a single
opening near ground level, and there is one above the roof height. Openings are controlled by
automatic louvers that close when in heating mode. The interior facade is double-pane low-E
glazing, and the exterior is single-pane clear glazing. Catwalks at each floor level allow access to
the cavity for maintenance, and also serve as shading devices. Light shelves and a movable
shading device within the cavity also serve to control light and heat entering the building. There
are no operable windows on the interior facade within the cavity, so the DSF serves only to
extract heat from the facade. Arup predicted a 21 percent savings in energy in the perimeter zone
adjacent from the facade from this configuration.
3.4.4.4 Multi story
In this DSF case, the cavity is adjoined vertically and horizontally by a number of rooms.
Ventilation occurs via large openings near the ground floor and roof. The room behind the DSF
should be ventilated mechanically (Osterle, 2001). For winter conditions, the cavity can be
closed at the top and bottom to take advantage of the greenhouse effect created in the cavity.
During summers, the cavity is kept open to exploit cooling buoyancy. Multistory facades are
suitable when external noise levels are high. However, high levels of sound transmissions that
occur in the intermediate space in this facade type are problematic. As shown in Figure 3.9 the
external skin is set independently in front of the inner facade. The intermediate space can be
ventilated in all directions. The other problem of such a facade is related to fire protection as all
the rooms are linked.
Another issue with this DSF type is that major thermal discomfort exists for the upper floor
chimney zone. In a multistory double skin facade, as a result of solar radiation, the air in the
44
intermediate space between the two skins becomes warmer than the external air. The air in this
space will therefore be lighter than outside air. The intermediate space is in contact with external
air at the top and bottom, so that a pressure-equalization process occurs. The cooler external air
is heavier and thus causes excess pressure at the bottom of the opening, which forces it into the
intermediate space. The warmer air within this space is lighter and rises upward, thus causing a
state of excessive pressure at the top, whereas the heated air provides less comfort in the upper
floors if not totally ejected.
(a) (b) (c)
Figure 3.14 Multistory DSF: Plan (a); section (b) and elevation(c) (Osterle, 2001)
Example of multi story DSSF: Occidental Chemical Center
Location: Niagara Falls, N.Y.
Building size: 20,000 𝑚2 ,12 stories
Building description: Office building
Architect: Cannon Design, Inc.
Consultants: Hellmuth, Obata, & Kassabaum
Figure 3.15 Occidental Chemical Building, southwest corner
45
This project, a renovation of an existing building with conventional glazed curtain walls, was the
first DSF building in North America. A second facade of green-tinted insulating glazing was
added to the exterior of all four facades, creating an undivided, and 1.2 meter-wide cavity that
extends the full height of the building. Motorized louvers control airflow through the cavity,
which is exhausted through an opening at the top above roof height. Details of these opening are
shown in Figure 3.12 above. There are wide, horizontal louvers for shading within the cavity
controlled by light sensors. The configuration and energy saving intent of this DSF design is
similar to that of the Seattle Justice Center, but the cavity is used to preheat air for the HVAC
system during the heating season. As in the Justice Center, there are no operable windows.
In 2001, Terri M. Boake and Kate Harrison of the University of Waterloo studied this building to
assess the DSF performance. The cavity was quite dirty due to lack of maintenance. The
automatically controlled louvers had not been functioning for about four years, and the
motorized dampers were covered with plywood. There was no airflow through the cavity, which
caused it to overheat; occupants complained of discomfort due to the malfunctioning system. The
faults were found to be largely a result of a failed control system.
3.5 Previous work
Double skin facade (DSF) is a concept that is being adopted on many new buildings in Europe
with the promise of saving energy while maintaining a transparent facade. Research, studies, and
several simulation programs have been carried out to explore solar chimneys—one way to
increment natural ventilation and improve indoor air quality—and Trombe walls prior to DSFs.
Gan (1998) studied Trombe walls for summer cooling of buildings. He used CFD to simulate
ventilation rates resulting from natural cooling. He also investigated the effects of the distance
46
between wall and glazing, wall height, and type of glazing. He concluded that, using trombe wall
for summer cooling by the buoyancy effect increased with the wall temperature, wall height and
thickness.
Afonso (2000) compared the behavior and air-exchange rate in a room with both a conventional
and solar chimney at different times of the year. He concluded that chimney wall thickness
should be chosen according to building utilization. A small thickness is optimal for diurnal
operation; for night operation, a larger thickness is advisable. He also mentions that as the nature
of wind is variable, the design of the solar chimney can be done without considering the wind
effect. Most of the studies using the stack effect idea or the solar chimney concept found that
passive summer ventilation is possible even in multi-story buildings. Due to the random nature
of the wind, these studies did not consider it in the simulation.
In the U.S., people are reluctant to use DSFs due to high first costs and the lack of a precise
airflow model that can accurately predict the facade performance. Arons (2000) developed a
model of performance and experimentation verification on a small-scale facade for a Japanese
climate.
An experimental study determining the performance of a single-story, south-facing DSF was
done at Virginia Technical Institute by Shang Shiou Li (2001). Two modular, full-scale double
glazed windows were naturally and mechanically ventilated and monitored for a range of
weather conditions. The results showed that the average cavity-heat removal rate of an active
system is 25 percent more than a naturally ventilated one. In addition, the temperature difference
between the indoor glass surface and indoor air was higher in the passive system.
Saelens (2002) also contributed to the energy performance assessment of single story, multiple-
skin facades that are naturally and mechanically ventilated. He undertook a controlled
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experimental set-up measure and provided data to compare and validate the numerical model. He
found that a traditional facade with shading devices were comparable to a naturally ventilated
DSF and a mechanically ventilated one.
Faggembauu (2003) did a numerical study on passive systems in general, and advanced the
concept of facades in particular. In the study, a transient code for the simulation of double and
single skin facades including advanced technological elements such as phase change materials,
transparent insulation, and facade integrated collectors was developed.
Gratia (2004c) attempted to look at the impact of DSFs that face south in a temperate climatic
condition. Thermal analysis using simulation software for different seasons of a year was
peformed for a low-rise office building with and without a DSF. The results indicated that
significant energy savings are possible if natural ventilation can be exploited by using DSFs.
Oesterle et al. (2001) compiled DSF typologies, advantages, disadvantages, uses and many
examples to prove this point. A parametric analysis of overheating in summer conditions in a
full-scale DSF laboratory chamber was carried out for this study. CFD was used to compare the
results with full-scale experimental models by Hernandez (2006).
Numerous papers have described how multiple skin facades should work to improve a building‘s
energy efficiency. Manz (2005) mentions that, ―Gertis correctly points out that only few
simulations have been made and that only few measurements are available to support the claimed
benefits. Much of the literature deals with specific topics such as the modeling of the convective
heat transfer in cavities or the optical properties of glass layers.‖
Most researchers provide models to simulate specific multiple skin facade typologies. Only a few
models for naturally ventilated multiple skin facades are available. Todorovic and Maric (1998)
used a single-zone heat balance representing an entire cavity. Faist (1998) developed a simplified
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iterative method to model the airflow due to the stack effect in multi-story envelopes. In this
model, the DSF acts like a solar chimney, extracting air through openings in the interior or
exterior skin. Wind effects were not considered (Saelens, 2002). He presents a limited evaluation
of the model with in situ and laboratory measurements. Van Paassen and van der Voorden (2000)
developed a network model in which airflow is based mainly on the stack effect. The model had
a limited capability to take into account airflow due to wind through joints distributed over the
height of the cavity (Saelens, 2002). Airflow from the cavity towards the building was not
considered. No comparison with other measurements was given. Results from CFD calculations
have become available only recently (Oesterle et al., 2001; McCarthy and Wigginton, 2002).
They are mainly illustrative and not yet validated. Moreover, wind effects are not taken into
account in these works.
A three-dimensional modeling of a single-story DSF was done with CFD to visualize the airflow
within a system (Hernandez, 2006). To date, however, little information is available on how
ventilated glazed facades behave during cold winters, or hot, humid summers. At the same time,
there has been a significant increase in the number of glazed facades applied to commercial and
office buildings. Various experimental and numerical investigations of air flows and heat transfer
in glazed cavities such as DSFs and of airflow patterns, temperature distributions, and heat flows
at solar-protection devices close to window glazing have been performed (Phillips et al, 2001;
Duarte et al., 2001). In the literature, numerous papers describe how DSFs should work to
improve a building‘s energy efficiency. Some authors sum up principles and ideas without
providing calculation results or experiments (Lieb, 2001; Den Boer and Ham, 2001; Arons and
Glicksman, 2001). Although many other articles representing a tremendous amount of work in
this area can be cited, Gertis (1999) stresses a continuing, significant lack of reliable verified
49
simulation techniques in the DSF domain for high-rise buildings. Other researchers have
provided models to simulate specific DSF typologies. However, they do not link envelope-level
results to building energy performance or couple the model to a building energy simulation
program (Saelens, 2002). Only a few combinations of DSF modeling and energy simulation are
available. Most of these papers are restricted to only one DSF typology. In this study, the focus is
in the energy saving objectives of a combination of two conventional typologies used in an office
in Chicago. The dissertation—which only deals with the thermodynamic and fluid-dynamic
behavior of naturally ventilated combined shaft-corridor configuration of DSF during shoulder
seasons in high rise office buildings— sets out to make a small contribution toward filling this
gap. The goal is to present a numerical investigation and to show an approach to model such
facades based on a computational fluid dynamics (CFD) model in a combined shaft-corridor
configuration of DSF in cavities with shading devices and to compare simulated results with
conventional facades. The dissertation will study natural ventilation in air supply and exhaust
mode and a double skin south-facing facade with a combination of two facade types, a shaft and
corridor type (the cavity height would be variable), in a high-rise office building.
3.6 Natural ventilation in double skin facade
A number of interesting investigations and findings are reported in the literature pertaining to
passive ventilation in buildings and the thermal performance of double skin facades. Even
though most of the research has been done in temperate climate conditions, the studies have
revealed a close link between natural ventilation design and the DSF function. It was found that
significant energy savings are possible if natural ventilation can be exploited through the use of a
DSF.
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For example, Grabe et al. (2001) developed a simulation algorithm to investigate the temperature
behavior and flow characteristics of double facades with natural convection through solar
radiation. It was found that the air temperature increased greater near the heat sources that were
near the panes of the window and the shading device. Gratia and Herde (2004a, 2004b, 2004c,
2004d, 2004e, 2007a, 2007b, 2007c, 2007d) attempted to look at natural ventilation strategies,
greenhouse effects, and the optimum position of sun-shading devices for DSFs facing in a
southern direction in a temperate climatic in the northern hemisphere. They found that sufficient
day-or night-ventilation rate can be reached by window opening, even if wind characteristics are
unfavorable. If natural cooling strategies are used with double facades, the greenhouse effect is
favorable if the facade is facing south. Thermal analysis using simulation software was done for
a low-rise office building with and without double-skin facade for different seasons. They also
provided some general guidelines in improving natural daytime ventilation in office buildings
with a DSF and demonstrated that efficient natural-cross ventilation is possible in climatic
conditions in Belgium.
3.7 Double skin facades in office buildings
The double skin facade is a system that can create opportunities for maximizing daylight and
improving energy performance. There are many issues to be considered in the development of
appropriate facade systems for an office building. A natural stack effect often develops in the
cavity and the facade can reduce solar gains as the heat load against the internal skin can be
reduced through the ventilated cavity. The relatively new double skin facade technology requires
greater care in implementation, especially for high-rise buildings.
The effects of wind and strong thermal uplift are two of the more important issues that need to be
dealt with in design. A precise survey of wind loads acting on buildings can be obtained through
51
measurements in a wind tunnel or by using appropriate simulation software. Intelligent control
mechanisms have been used in most double skin facade buildings to regulate the admittance of
air into the cavity automatically and also closing it up to create a thermal buffer. Further details
of important issues in designing double-skin facades for high-rise office buildings are discussed
below.
3.8 Conclusion
In this chapter, a definition of double facades is given. A brief history and DSF examples are
presented, and existing typologies are outlined. The typology is based on the origin, the driving
force of the airflow, and divisions of the facade. It also allows for a description of how a DSF
might operate. Based on the literature review, the developments of studies using DSF and other
quantitative methods of analysis are reviewed and linked to energy perform. Previous work by
various authors has been studied and highlighted in this chapter. A new DSF configuration,
which is a combination of two typical facades, follows this chapter. The energy and thermal
performance assessment of this configuration in Chapter 6 will put this research into a broader
perspective.
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Chapter 4.0
Application of Computational Fluid Dynamics in Architecture
4.1 Introduction
Natural ventilation is an essential part of sustainable building design. Energy conscious designers
harness the cooling capacity of natural wind to increase indoor thermal comfort and ultimately
save energy for active-space conditioning. Wind can cause air movement and perception of
cooling, wind can bring in air of a different temperature and humidity. By numerically solving a
series of conservation equations related to mass, momentum, and energy, computational fluid
dynamics (CFD) tools help designers predict detailed airflow for special design cases and plan a
building with optimal natural ventilation. This chapter will describe CFD and how to use two
programs commonly involved in CFD: Fluent and Gambit.
4.2 Application of CFD for building design
Knowledge is often needed about the pattern of airflow and distribution of air temperature within
an enclosed space. This may be especially important in checking the performance of a natural
ventilation system to predict comfort. Different techniques can be used to study the wind effect
in building design, such as a model mockup, wind tunnel, nodal/zonal models, and
computational fluid dynamics (CFD). It is often inconvenient to evaluate full-scale (model
mockup) buildings in the design or occupancy phase of a building, so models are created to
simulate the airflow. The goal of modeling is to evaluate systems in feasible, economical way.
Modeling techniques have been used to investigate flow around objects and within spaces and
buildings in a wide variety of systems.
53
Three types of models are currently used: mathematical models that provide an analytical
solution; computational models that provide a numerical solution; and physical models used for
experimental solutions. Analytical solutions are mathematical analyses that describe the
phenomena under investigation through a series of equations. An analytical solution is assumed
to have a closed-form solution, in that at least one solution can be expressed as a mathematical
expression in terms of a finite number of well-known equations. The governing, analytical flow
equations for buoyancy, wind, and combined flow were presented in Chapter 2. They are
applicable to simple configurations and geometries with well-mixed assumptions and a limited
number of zones, such as a single room attached to a double skin facade (DSF) system.
The numerical solution is a more complex version of the mathematical model described above,
in that it is a system of algebraic relationships that are solved simultaneously. The computational
model provides point-like solutions, with unique values for a series of determined points. A
common approach to numerical solution in the area of ventilation is the use of CFD software to
quantitatively predict fluid flow in or around objects. CFD software programs such as Fluent
have the ability to model temperature interactions, heat flow, buoyancy, and air flow in and
around buildings. A grid of boundary surfaces and inclosed space is used to solve the mechanical
and thermodynamic relationships throughout the environment under analysis, taking into account
the layout, ventilation opening(s), geometry, and heat loads (Szucs, 1980).
CFD applications representing the flow field have become increasingly popular. CFD is a
numerical method that approximates the enclosure by a series of control volumes. Air flow in
each element must follow fundamental physics laws covering energy transport, conservation of
mass, and momentum. These conservation equations are solved for all nodes of a cellular grid
that is placed within the domain. Specific applications for CFD include the simulation and
54
prediction of temperature distribution, air velocity distribution (for comfort, draughts, etc.),
pressure distribution, airflow in large enclosures (DSF, atria, airports, etc.) and airflow around
buildings (for wind pressure distribution).
4.2.1 CFD approaches in an indoor environment simulation
CFD programs, in particular, can be used to deal with problems associated with the thermal
environment, indoor air quality, and building safety as they estimate important parameters such
as temperature, airflow, and relative humidity. CFD applications in indoor environments are very
diverse and there are many recent examples of its use for natural ventilation design (Carrilho da
Grace et al., 2002), the study of building material emissions for indoor air quality assessment
(Murakami et al., 2003), building elements design (Manz, 2003) and for building energy and
thermal comfort simulations (Bartak et al., 2002; Beausoleil-Morrison, 2002; Zhai and Chen,
2003).
4.2.1.1 Thermal comfort
By numerically solving the governing equations for fluid flow, CFD provides spatial-and
temporal-distributed information of airflow, pressure, temperature, turbulence intensity, and
moisture and contaminant concentration. These details can be used to evaluate the levels of
thermal comfort, indoor air quality, and building system energy efficiency. Air velocity,
temperature, and humidity ratio are the most important parameters in determining the predicted
percentage dissatisfied (PPD) distribution in a building (Zhai, 2005).
Achieving an acceptable indoor environment with respect to energy use is one of the most
difficult tasks when an office building is designed, especially if it is highly glazed. The main
components that define the indoor environment are shown in Figure 4.1.
55
Figure 4.1 Components of thermal comfort
• Temperature and radiation (dry bulb, mean radiant):
Thermal sensation is dominated by the surrounding temperature. The standard dry bulb
temperature, however, is not always a sufficient indicator for establishing a good indoor thermal
environment, as it does not take into account the influence of radiant energy. The mean radiant
temperature is a more appropriate thermal comfort indicator, as it is a measure of the average
radiation exchange between the occupant and the surrounding surfaces.
• Relative humidity: Relative humidity is the ratio of moisture content at a certain temperature to
the maximum possible moisture content at that temperature (until condensation starts).
Generally, humidity affects heat loss by evaporation, which is most important at high
temperatures and high metabolic rates (ASHRAE Fundamentals, 2005).
However, questionnaires have shown that even in comfort zones relative humidity has a large
impact on the perception of the thermal environment. High relative humidity means that the
moisture content of clothing increases, which alters their insulating properties. Usually the
relative humidity in an office space varies between 30 and 60 percent.
• Air velocity and turbulence: The sensation of thermal comfort is influenced by air velocity
and the scale of turbulence. Often the increased velocity can be an advantage in an office space,
where the temperatures are higher than the comfort range. A typical way to increase air velocity
Thermal
Comfort
Mean
Radiant
Temperature
Mean Air
Temperature
Relative
humidity
Air flow Clothing Activity
level
56
is to use circulation fans. However, at other times, draughts cause discomfort due to localized
cooling.
• Clothing: Clothing provides thermal insulation and thus has an important influence on
acceptable temperature. The choice of clothing can alter comfort preferences by as much as 2 to
3°K. The unit that expresses clothing insulation is clo; (1clo = 0.155 𝑚2K𝑊−1). According to
the 2001ASHRAE Handbook Fundamentals, ―because people change their clothing for the
seasonal weather, ASHRAE Standard 55 specifies summer and winter comfort zones appropriate
for clothing insulation levels of 0.5 and 0.9 clo respectively.‖
• Activity: activity level results in metabolic rates between 1.0 met and 1.3 met for office
building.
• Operative and resultant temperatures: The operative and mean resultant temperatures
empirically combine the dry bulb and the mean radiant temperatures. The operative temperature
is the temperature at which a person emits the same heat output as before, but when air
temperature (Ta) = radiant temperature (Tr) = operative temperature (Top) (Peterson, 1991). The Top
does not have the same value for all parts of the room. Acceptable operative temperature ranges
for naturally conditioned spaces
Figure 4.2 Relation between operative temperature and humidity
57
Distribution of winter indoor climatic measurements on the ANSI/ASHRAE Standard 55-1992
comfort chart defined in terms of ET (an Effective Temperature, ET*, that is the dry-bulb temperature
of a hypothetical environment at 50% relative humidity and uniform temperature (Ta = MRT) where the
subjects would experience the same physiological strain as in the real environment.), dewpoint
temperature and RH or wet bulb temperature. The chart on the left shows the comfort zone
before the 1995.
Air speed < 0.2m/s
Difference between radiant & air temp < 4 °𝐶 Top = A Ta + (1-A) Tr
V <0.2m/s 0.2-0.6m/s 0.6-1m/s
A 0.5 0.6 0.7
Table 4.1 Thermal Environment Conditions for Human Occupancy from ANSI/AHRAE Standard55-2004
• Perception of thermal comfort: It is important to clarify that thermal-comfort conditions are
not easy to define, as it is a very subjective value. Thus, a thermal environment that is acceptable
to some people may be totally unacceptable to others. According to Andresen (2000), it is not
only that people are differently dressed and have different metabolic rates, but their assessment
of comfort is also influenced by their psychosocial environment, which cannot easily be taken
into account by any calculation method. The most commonly used calculation methods are the
ASHRAE standard 55 (ASHRAE, 1992) and the ISO Standard 7730 (ISO, 1984). In order to
describe this factor it is necessary to explain the concepts of predicted mean vote (PMV) index
and predicted percent dissatisfied (PPD). Both ASHRAE and ISO standards are based on the
concepts of PMV and PPD as developed by Fanger (1970).
The PMV index is a measure of thermal sensation, since it expresses the correlation between
indoor environment parameters and human sensation of thermal comfort. It is a function of
58
activity, clothing, air temperature, mean radiant temperature, relative air velocity, and humidity.
As described in ASHRAE Fundamentals (2001), ―The PMV index predicts the mean response
of a large group of people according to the ASHRAE thermal sensation scale.‖ The ASHRAE
sensation scale is presented below:
+3 = hot, +2 = warm, +1 = slightly warm, 0 = neutral, -1 = slightly cool, -2 = cool, -3 = cold.
The PPD of a large group is an indication of the number of persons who will be inclined to
complain about the thermal conditions. After estimating the PMV, the PPD can also be
estimated. Those persons not scoring +0.5, -0.5, or 0 are deemed to be dissatisfied. From this, the
PPD of occupants can be determined. Liddament (1996) writes that, ―the immediate conclusion
of this work was that it was not possible to define a set of thermal conditions that would satisfy
everyone. Even when the average of the predicted mean vote was zero, i.e. a neutral thermal
environment, 5% of the test occupants were dissatisfied.‖ Accepting that no single environment
is judged satisfactory by everybody, the standards specify a comfort zone based on 90 percent
acceptance or 10 percent dissatisfied occupants. Thus, the upper limit for operative temperature
in summer is 26°C, given 50 percent relative humidity, sedentary activity, 0.5 clo and a mean air
velocity of less than 0.15 m/s.
Based on the PMV index, the PPD index can be calculated. The PPD index predicts the
percentage of occupants who will judge their thermal comfort unsatisfactory (corresponding to a
vote below –2 or above +2). PPD as a function of PMV is shown in the functions below:
PPD is a major index for building thermal comfort judgment. It can be calculated via (4.1):
PPD= 100−95 Exp(0.03353 𝑃𝑀𝑉4 - 0.2179 𝑃𝑀𝑉2
) [%]. (4.1)
The PMV in the equation is determined by:
59
PMV= [0.303Exp ( 0.036M) 0.028] L (4.2)
where M is body metabolism (W·𝑚−2) and L is thermal load on the body (W·𝑚−2).
M and L are the functions of air velocity, temperature, humidity ratio, and enclosure temperature.
In addition, CFD results can be used to calculate the distribution of percentage dissatisfied (PD)
people due to draft, another major thermal comfort index, through the equation:
PD = (34−T) (U − 0.05) 0.62 (3.14−0.37U Tu) [%] (4.3)
where T is local air temperature (°C), U is local air speed (m·𝑠−1), and Tu is turbulence intensity
(%). If the turbulence kinetic energy k (𝑚2·𝑠−2) is simulated by a turbulence model, the
turbulence intensity can be estimated as:
Tu=100(2k) 0.5/U [%] (4.4).
CFD programs such as Fluent can provide detailed predictions of thermal comfort and indoor air
quality, such as air-velocity distribution, temperature, and relative humidity. The distribution can
be used further to determine thermal comfort and air quality indices such as described above plus
the PMV, the PPD, and the PD.
4.2.2 CFD approaches in an outdoor airflow simulation
A CFD program can also calculate the pressure difference around buildings and these data can be
used it as boundary conditions2 for subsequent indoor airflow simulation. Ideally, the calculation
should be performed for different wind directions under various wind speeds in a period suitable
for natural ventilation, such as spring. For a site in Chicago Figure 4.3 illustrates pressure
distribution pattern under a prevailing wind direction (southwest) and speed (10 m/s). In order to
correctly take the impact of the surrounding buildings into account, the computational domain is
much larger than the one shown in the Figure. Clearly, the pressure difference is the highest
between the northern and southern facades. It is also interesting to note that CFD can help
2 The set of conditions specified for the behavior of the solution to a set of differential equations at the boundary of
its domain
60
develop natural ventilation by modeling and optimizing building site plans and indoor layouts.
Jiang and Chen (2002) found that the outdoor environment has a significant impact on the indoor
environment, especially in buildings with natural ventilation. They recommended that both the
indoor and outdoor environments along with the combined indoor and outdoor airflow need to be
studied together.
Figure 4.3 Urban pressure distribution (Wolf Point Chicago and surroundings)
4.2.3 CFD approaches in facade design
In the case of a naturally ventilated double-skin facade (DSF), wind speed and wind direction are
important data required for correctly predicting the ventilation around and within a building. The
facade system‘s solar performance is also critical as well as detailed solar-radiation data, which
can be learned through building-energy simulation tools, such as EnergyPlus. Since these
parameters are the driving force for natural convection, detailed data are required to study natural
ventilation. A further difficulty is the prediction of the airflow rate in the facade cavity due to
combined buoyancy (stack effect) and wind effects in natural convection. The airflow rate at any
point is unknown and depends on the temperature profiles. This combined effect of wind and
61
temperature differences creates a pressure difference between the facade‘s inlet and outlet, which
determines the airflow rate in the facade cavity. When wind velocities are low, the stack effect
will be dominant; if wind velocities are high the wind effect will dominate. There is a
―transition‖ regime between both effects that may assist or counteract the overall natural
convection conditions.
Figure 4.4 The effects of combined wind and stack forces: (a) reinforcing vs. counteracting effect (b)
depiction of counteracting wind and stack effect over a progression of wind speeds (Alloca et al., 2003)
Fluent can calculate both driving forces through control volume system. Grabe et al. (2001)
carried out a detailed study of the effects of ventilation with double-skin facades which provides
important guidelines in using CFD simulation for facade investigation. They determined that the
simulation of a double-skin facade must yield the following information:
a) The air mass flow through the facade gap to control the possibility of natural ventilation of the
room behind.
b) The temperature of the facade air related to its height determines the temperature of the supply
air in natural ventilation. It also helps in estimating the cooling load required in the case of air
conditioning.
62
4.3 Simulation approach: Model set up
4.3.1 Fundamental of airflow modeling
Key parameters calculated as part of a CFD analysis include:
Pressure distribution
Airflow is driven by pressure distribution; therefore the pressure field is fundamental to the
whole flow process. Pressure is maintained by a combination of driven air or forced convection
and buoyancy forces or natural convection. Free convection is driven by buoyancy forces created
by an imbalance in temperature difference.
Velocity field
Air movement is a vector having components in both speed and direction. To determine the air
velocity distribution, air flow must usually be represented by three transport equations.
Temperature field
The temperature field is sustained by thermal sources and sinks distributed about the enclosure.
Buoyancy forces and free convection currents are generated by the temperature field.
Boundary layer flow
Air flow close to surfaces is subjected to boundary later effects in which the rate of flow is
influenced by surface friction.
User input-boundary conditions
Flow, turbulence, temperature, and pollutant fields are unique to the prevailing boundary
conditions. Input data must include:
- Location of openings
- Mass flow into and out of the building
- Type of flow boundary
- Velocity (speed and direction of flow through each opening)
- Thermal properties of surfaces and/or surface temperatures.
63
Figure 4.5 The schematic diagram of the office module's inputs: 1)upper air outlet to chimney; 2) interior
upper operable window; 3) controllable solar control device; 4) interior operable or fixed view window;
5) exterior glazing layer; 6) air cavity; 7) interior
4.3.2 Creating a model geometry for CFD
In order to analyze the CFD model, geometry needs to be created in Gambit (Gambit is a
meshing software program), which uses discrete points to describe the space. The Gambit model
and the mesh grid are then exported to Fluent in order to conduct the CFD analysis.
4.3.2.1 Finite volume grid and geometric modeling considerations
To understand the model‘s applicability to architectural projects, it is important to understand
what assumptions were made in the models and how researchers determined that they were
satisfactory. The scope of CFD models includes modeling the DSF ventilation across the width
of a floor plate, for a typical floor plate area, with three chimneys. Models are considered
accurate once they have run a sufficient number of iterations as described by the researchers. In
Fluent code, residuals are reported for each conservation equation. A discrete conservation
equation at any cell can be written in the form LHS = 03. For any iteration, if one uses the current
solution to compute the LHS, it won‘t be exactly equal to zero, with the deviation from zero
3 The LHS describe time rate of change of velocity and momentum flux.
4
1
2
3
5
6
7
8
64
being a measure of how far one is from achieving convergence. So Fluent calculates the residual
as the (scaled) mean of the absolute value of the LHS over-all cells. Residual is the measure of
farness from the conservation equation answer, typical number in architectural applications is
less than 10−3. As Hernandez (2006) mentioned that "Simulations were considered converged
when the normalized residuals were smaller than 10−3and the solution field was stable. i.e. the
values did not change by more than 10−7(relative change) between iterations, and showed no
visible fluctuation or changes after hundreds of iterations. The effects of turbulence were
modeled using the standard k-e model. Results of simulations for different flow rates showed a
linear variation of the air speeds in the room with inlet speed, as expected.”
4.3.2.2 Modeling and solvers
A practical approach to predict outdoor airflow is to decouple the outdoor and indoor airflow
simulation. Outdoor airflow around buildings is first predicted and provides airflow and pressure
information at the openings of buildings. With these values as the boundary conditions, indoor
airflow for each space can be simulated independently and natural ventilation rate can be
determined.
The decoupled simulation method is based on the assumption that indoor airflow and building
openings have little impact on outdoor airflow and pressure distributions; indoor and outdoor
flow fields can therefore be studied separately.
Stankovic4 (2007) found that the accuracy of CFD results is critically dependent on boundary
conditions. The highest accuracy of the boundary conditions is normally achieved by combining
the measured specific site data with dynamic thermal simulations.
4 Internet page of Technology, Environmental Engineering in the Tropics, http://www.sia.org.sg
65
Jaros et al. (2002) established that the CFD characteristics of solved problems could be grouped
under the following:
—where fluid flow is predominantly driven by buoyancy forces (natural or mixed convection);
—where heat transfer arrives simultaneously by conduction (in solids), convection, and
thermal/solar radiation (in fluid).
The correct type of fluid flow is a very important aspect of the CFD simulation as well.
There are two radically different states of flows that are easily identified and distinguished:
laminar flow and turbulent flow. Laminar flows are characterized by smoothly varying velocity
fields in space and time in which individual ―laminar‖ (sheets) move past one another without
generating cross currents. These flows arise when the fluid viscosity is sufficiently large to damp
out any perturbations to the flow that may occur due to boundary imperfections or other
irregularities. These flows occur at low-to-moderate values of the Reynolds number5. In contrast,
turbulent flows are characterized by large, nearly random fluctuations in velocity and pressure in
both space and time. These fluctuations arise from instabilities that grow until nonlinear
interactions cause them to break down into finer and finer whirls that eventually are dissipated
(into heat) by the action of viscosity. Turbulent flows occur in the opposite limit of high
Reynolds numbers.
The solver needs for this study are more likely to be turbulent due to irregularities of the surface.
There are usually regions with and without turbulence in the same space. The turbulence model
must be able to deal with laminar and transitional flow at the same time and the RNG k-e model
of turbulence appears to be the most suitable choice among other models in Fluent.
5 Reynolds number can be defined for a number of different situations where a fluid is in relative motion to a
surface. (from Wikipedia: http://en.wikipedia.org/wiki/Reynolds_number).
66
Gan (1995a, 1995b) has carried out detailed research into the effects of displacement ventilation
in building design using CFD simulation. He used the standard k-e turbulence model for the
prediction of indoor air flow patterns, temperature and moisture distributions while taking
account of heat transfer by conduction, convection, and radiation. The thermal comfort level and
draught risk are predicted by incorporating Fanger‘s comfort equations in the airflow model. He
found that common complaints of local thermal discomfort in offices with low turbulent air flow
such as displacement ventilation often results from unsatisfactory thermal sensation rather than
draught itself or alone.
In his research on thermal transmission through DSFs, Gan (2001) used CFD for predicting the
convective heat transfer coefficient, thermal resistance, and thermal transmittance for a double-
glazed unit. The unit was an unventilated enclosure and the flow within it would be buoyancy-
induced natural convection.
Navier-Stokes (RANS) equation models and Large Eddy Simulation (LES) models to enhance
the capabilities of CFD for use in indoor and outdoor environment design are used in Fluent.
A two-layer turbulence model, a single k- E equation turbulence model for near-wall flow, and
the standard k-e model for flow in the outer-wall region could accurately predict heat transfer on
a wall. The computing time needed is slightly higher than the standard k-e model but much lower
than a low-Reynolds number k-e model. A zero equation model (a single algebraic function) is
used to simulate transient flow that significantly reduces computational time. The coupling with
an energy simulation program gives more accurate results for building energy analysis and
indoor environment design. A new dynamic sub-grid-scale model is used to predict indoor
airflow without a homogenous flow direction. The model uses two different filters to obtain the
67
model coefficient as a function of space and time. The model can accurately predict flow in a
room with a heated floor and in an office with displacement ventilation.
The space to be simulated is discretized into a set of control volume or elements. The enclosed
space may be divided into 30,000 to 50,000 control volumes or more, so each element represents
only a fraction of the total enclosure volume. The system of discretization can be non-uniform so
that clusters of elements can be located at areas of greatest interest. Direct solution techniques
are not available, therefore iteration is applied. All parameters are initially given arbitrary values
for which the iteration can commence. These values are then adjusted until each of the transport
equations balance. The process of reaching a balance is referred to as convergence.
The accuracy of CFD prediction is highly sensitive to the boundary conditions supplied
(assumed) by the user. The boundary conditions for CFD simulation of indoor air flows relate to
the inlet (supply), outlet (exhaust), enclosure surfaces, and internal objects. The temperature,
velocity, and air turbulence entering from diffusers or windows determine the inlet conditions,
while the interior-surface, convective-heat transfers in terms of surface temperatures or heat
fluxes are for the enclosures. These boundary conditions are crucial for the CFD accuracy.
Figure 4.6 The air path inside the double skin facade transition from laminar to turbulent flow
Laminar flow
Turbulent flow
68
4.3.2.3 A model grid in Gambit
The calculation method requires that the geometric space across which the calculations are to be
conducted is first divided into a number of non-overlapping, adjoining cells which are
collectively known as the finite volume grid.
When a CFD project is created, a grid is automatically generated for the required model domain
by identifying all contained model object vertices, and then generating key coordinates from
these vertices along the major grid axes. These key coordinates, extended from the X, Y, and Z
axes across the width, depth, and height of the domain, respectively, are known as ―grid lines.‖
The distance between grid lines along each axis is known as a grid region and these regions are
initially spaced employing user-defined, default grid spacing to complete the grid generation.
The grid can have three different shapes but for a building application, a non-uniform rectilinear
Cartesian grid would usually be used as shown in Figure 4.8, which means that the grid lines are
parallel with the major axes and the spacing between the grid lines enables non-uniformity.
By default, grid regions are spaced uniformly using a system that is calculated to be as close as
possible to the user-defined default grid spacing. In this case, the distance between these key
coordinates is of an acceptable value. However, very narrow regions resulting in long, narrow
grid cells or cells having a high aspect ratio should be avoided, as they tend to result in unstable
solutions that can fail to converge. Highly detailed component assemblies can result in very large
numbers of closely spaced key coordinates resulting in cells having high aspect ratios. Large
numbers of key coordinates can also lead to overly complex grids and correspondingly high
calculation run times and excessive memory usage, which can be avoided by replacing very
detailed assemblies with cruder representations for the purpose of CFD calculation. However,
where very narrow grid regions are unavoidable, adjacent grid lines formed from key coordinates
69
can be merged together using the merge tolerance setting which is accessed through the new
CFD analysis dialogues.
Figure 4.7 The mesh generated for a combined shaft-corridor DSF in Gambit.
As shown in Figure 4.8 the mesh has been mapped quads or triangles(unstructured solver). The
number of grid is almost 5 million cells.
4.3.3 Boundary conditions of the three-dimensional model
An important initial concept for CFD analyses is that of boundary conditions. Each of the
dependent variable equations requires meaningful values at the boundary of the calculation
domain in order for the calculations to generate meaningful values throughout the domain. These
values are known as boundary conditions, and can be specified in a number of ways. The
specification of boundary conditions for two driving forces of wind and buoyancy effect can be
defined as a pressure difference on inlet and outlet. To calculate the stack effect, the energy
equation needs to be turned on (Fluent doesn‘t solve energy equations by default). By then
setting the gravity vector correctly, the Boussinesq approximation calculates the natural
convection effect. One drawback of this method is that it greatly slows down Fluent‘s solution-
70
convergence rate. Regarding the outdoor wind, by specifying pressure inlet and outlet conditions,
the dynamic pressure of wind will be taken care of, therefore the outflow wind effect can be
specified effectively there.
4.3.3.1 Wind speed, wind direction, and mean wind speed profile
The natural wind speed varies in time and space; the character of its variation is highly random
and the wind flow is highly turbulent. At the same time, the wind speed is one of the main
contributors to natural ventilation flow. The change of the mean wind velocity depending on
height and intervening terrain is expressed through the mean wind speed profile, as one of the
boundary conditions. Mean wind speed data for a specific time period is going to be used as one
of the boundary conditions for the study, as stated in the previous section.
4.3.3.2 Outdoor air temperature, air humidity, and solar radiation
The mean outdoor air temperature is one of the other climate parameters that is required for the
boundary condition. The table 4.2 shows a sample of the boundary conditions input.
71
Domain
Domain Material Incompressible flow-Air at 20°C, 1 atm
Reference Pressure 100,000 Pa (atmospheric pressure)
Reference Temperature 288 K
Sources
Buoyancy Model
Boussinesq - calculates airflow from
density difference
Buoyancy Reference Temperature Outdoor air temperature in the specific time and date
Gravitational Acceleration -9.81 m/s in the y-direction
Wind as the driving force Wind velocity based on the external CFD modeling and
weather date
Boundary Conditions
Inlet
Outlet
Inlet pressure = static pressure +
Outlet pressure = Gauge pressure(static)
Wall boundary conditions Adiabatic solids (concrete)
glass: standard 6mm clear glass for external and double
low-e for internal layer
Velocity inlet 5 m/s
Cavity Details
Cavity Size 3.5m high by 7m wide by 1.5m deep
Cavity External Facade Internal plate with surface temperatures on both
sides is going to be calculated based on heat source
Cavity Internal Facade External plate with surface temperature base on heat
source
Table 4.2 Boundary condition sample
4.4 Solution procedure
There are four turbulence models available in Fluent: the mixing length zero-equation model, the
indoor zero-equation model, the two-equation (standard k-e) model, and the RNG k-e model. In
turbulent flows, it computes the mass diffusion in the following form:
72
𝐽𝑖 = − 𝜌𝐷𝑖 ,𝑚 +𝜇 𝑡
𝑆𝑐𝑡 ∇𝑌𝑖 (4.5)
where Sct is the turbulent Schmidt number, (with a default setting of 0.7).
In order to solve for buoyancy-driven flows and natural convection Fluent uses either the
Boussinesq model or the ideal gas law in the calculation of natural convection flows. The
importance of buoyancy forces in a mixed convection flow can be measured by the ratio of the
Grashof and Reynolds numbers as follow:
𝐺𝑟
𝑅𝑒 2=
𝑔𝛽∆𝑇𝐿
𝑣2 (4.6)
The terms radiant heat transfer and thermal radiation are commonly used to describe heat transfer
caused by electromagnetic waves. All materials continually emit and absorb electromagnetic
waves or photons. The strength and wavelength of emissions depends on the temperature of the
emitting material. At absolute zero K no radiation is emitted from a surface. Fluent only consider
the wavelengths in the infrared spectrum for heat transfer applications in its simulation and it
provides two models for radiation heat transfer simulations, namely the surface-to-surface (S2S)
radiation model and the discrete ordinates (DO) radiation model.
Fluent solves the governing integral equations for mass and momentum, and, when appropriate
for energy, species transport, and other scalars such as turbulence. In summary, a control
volume-based technique is used with the procedures as follows:
a) Division of the domain into discrete control volumes using a computational grid.
b) Integration of the governing equations in the individual control volumes to construct algebraic
equations for the discrete dependent variables such as velocities, pressure, temperature, and
conserved scalars.
c) Linearization of the discretized equations and solution of the resultant linear equation system
to yield updated values of the dependent variables.
73
Figure 4.8 The CFD procedure of modeling to be converged
The governing equations continuity, momentum and energy are solved by Fluent:
Continuity: 𝜕𝜌
𝜕𝑡+
𝜕(𝜌𝑢 )
𝜕𝑥+
𝜕(𝜌𝑣 )
𝜕𝑦+
𝜕(𝜌𝑤 )
𝜕𝑧= 0 (4.7)
X-Momentum: 𝜕(𝜌𝑢 )
𝜕𝑡+
𝜕(𝜌𝑢2)
𝜕𝑥+
𝜕(𝜌𝑢𝑣 )
𝜕𝑦+
𝜕(𝜌𝑢𝑤 )
𝜕𝑧= −
𝜕𝑝
𝜕𝑥+
1
𝑅𝑒 𝜕𝜏𝑥𝑥
𝜕𝑥+
𝜕𝜏𝑥𝑦
𝜕𝑦+
𝜕𝜏𝑥𝑧
𝜕𝑧 (4.8)
Y-Momentum: 𝜕(𝜌𝑣)
𝜕𝑡+
𝜕(𝜌uv )
𝜕𝑥+
𝜕(𝜌𝑣2)
𝜕𝑦+
𝜕(𝜌𝑣𝑤 )
𝜕𝑧= −
𝜕𝑝
𝜕𝑦+
1
𝑅𝑒 𝜕𝜏𝑥𝑦
𝜕𝑥+
𝜕𝜏𝑦𝑦
𝜕𝑦+
𝜕𝜏𝑦𝑧
𝜕𝑧 (4.9)
Z-Momentum: 𝜕(𝜌𝑤 )
𝜕𝑡+
𝜕(𝜌uw )
𝜕𝑥+
𝜕(𝜌𝑣𝑤 )
𝜕𝑦+
𝜕(𝜌𝑤2)
𝜕𝑧= −
𝜕𝑝
𝜕𝑧+
1
𝑅𝑒 𝜕𝜏𝑥𝑧
𝜕𝑥+
𝜕𝜏𝑦𝑧
𝜕𝑦+
𝜕𝜏𝑧𝑧
𝜕𝑧 (4.10)
Energy: 𝜕(𝐸𝛾 )
𝜕𝑡 +
𝜕(𝑢𝐸𝛾 )
𝜕𝑥 +
𝜕(𝑣𝐸𝛾 )
𝜕𝑦 +
𝜕(𝑤𝐸𝛾 )
𝜕𝑧 = −
𝜕(𝑢𝑝 )
𝜕𝑥−
𝜕(𝑣𝑝)
𝜕𝑦−
𝜕(𝑤𝑝 )
𝜕𝑧−
1
𝑅𝑒 𝑃𝑟 𝜕𝑞𝑥
𝜕𝑥+
𝜕𝑞𝑦
𝜕𝑦+
𝜕𝑞 𝑧
𝜕𝑧 +
1
𝑅𝑒
𝜕
𝜕𝑥 𝑢𝜏𝑥𝑥 + 𝑣𝜏𝑥𝑦 + 𝑤𝜏𝑥𝑧 +
𝜕
𝜕𝑦 𝑢𝜏𝑥𝑦 + 𝑣𝜏𝑦𝑦 + 𝑤𝜏𝑦𝑧 +
𝜕
𝜕𝑧 𝑢𝜏𝑥𝑧 + 𝑣𝜏𝑦𝑧 + 𝑤𝜏𝑧𝑧 (4.11)
74
The governing equations are solved sequential, and because the equations are not linear, several
iterations of the solution loop must be performed before a converged solution is obtained. Each
iteration consists of the steps outlined below and illustrated in Figure 4.9.
Fluid properties are updated based on the current solution. If the calculation has just begun, the
fluid properties will be updated based on the initialized solution.
b) The u, v, and w momentum equations are each solved in turn using current values for pressure
and face mass fluxes, in order to update the velocity field.
c) Since the velocity obtained in Step (b) may not satisfy the continuity equation locally, a
Poisson-type equation for the pressure correction is derived from the continuity equation and the
linearized momentum equations. This pressure correction equation is then solved to obtain the
necessary corrections to the pressure and velocity fields and the face mass fluxes such that
continuity is satisfied.
d) Where appropriate, equations for scalars such as turbulence, energy, species, and radiation are
solved using the previously updated values of the other variables.
e) A check for convergence of the equation set is made.
f) The above steps are continued until the convergence criteria are met. (Fluent Tutorial)
Figure 4.10 shows how the residuals for each variable changes based on the number of iterations
and reaches convergence.
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Figure 4.9 Convergence of residuals
4.5 Interpretation of CFD results
The simulation runs for an initial number of 1200 iterations typically. Then residuals will be
plotted to check the residuals in the boundary definition would be converged. The simulation
needs to be extended with at least all the residuals showing approximation to residuals of 1𝑒−8. It
is also necessary to carefully review the boundary settings and software mesh to solve the
problem or trend to diverge of the continuity residual. As a result, the temperature can be plotted
to illustrate the inlet-outlet temperature gradient. Also air-velocity magnitude inside the domain
shows the influence of the convective forces. The results of the CFD simulation then can be used
to calculate the thermal comfort based on the formula described at the beginning of this chapter.
Figure 4.11 illustrates the example of the CFD results-Velocity profile within the DSF and the
results show that the velocity in the offices is less than 1 m/s.
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Figure 4.10 Velocity vector profile in the combined shaft-corridor DSF office spaces
4.6 Conclusions of CFD modeling
This chapter has provided background on CFD and demonstrated using Fluent to model airflow
in buildings. The CFD modeling proved that airflow behavior could not have been intuitively
estimated or assumed by the design team without the use of such tools. The major impact of CFD
on the design is better airflow, and improved occupant satisfaction. In addition, the CFD was
used to verify the effectiveness (avoiding high velocities and stagnation) of the airflow patterns
at different wind speeds.
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Chapter 5.0
Methodology
In previous chapters the principles of natural ventilation and DSF system was discussed and the
application of CFD in built environment presented. This chapters provides the research
methodology for the examining various parameters in the design of a combined shaft-corridor
DSF investigating the energy performance through EnergyPlus and the behavior of airflow and
an analysis of internal thermal comfort levels through CFD simulations.
In addition, this chapter presents the knowledge gap and research goals for the study. This will
then lead to a discussion of the findings. The goal is to provide a process that can be applied at
the earliest design stage to help a designer make better decisions that will result in more energy
efficient buildings.
5.1 Introduction
This thesis addresses two major areas in energy efficient building design: technological aspects
of airflow modeling and energy performance. Fig. 5.1 describes the methodology followed in
conducting this research.
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Figure 5.1 Diagram for methodology conducted in this research
5.2 Goals of the research
In attempting to answer the research questions raised in the Introduction, extensive research into
the relevant subjects was carried out. The literature review was used to narrow the scope of the
research field, and further, to come up with the right questions in identifying the knowledge gap.
Issues such as natural ventilation strategies, human thermal comfort requirements, DSF
technologies, building simulation tools, high-rise building designs in the urban context, and other
built-environment criteria related to the research topic have been studied and critically reviewed.
The research is attempting to incorporate natural ventilation techniques, combined with newly
developed DSF technologies, and apply them onto high-rise office buildings in Chicago. A series
of guidelines for DSF designs for Chicago high-rise office buildings are proposed to help
designers make better decisions. This research will also help designers to make better selections
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of DSF design featuers in terms of openings, sizes and locations, cavity depth, height of shaft,
etc.
DSF energy-performance modeling is a complex problem. An accurate assessment of airflow
and temperatures within the cavity requires detailed analyses of solar radiation transmitted
through glazed facades, buoyancy, and wind pressure. Annual building simulation programs
cannot provide accurate CFD simulations. For that reason, we discuss the application of CFD in
the built environment in chapter 4.
The final objective of the research is to contribute to the energy performance and thermal
comfort assessment of a combined shaft-corridor DSF by means of energy dynamic simulation
and CFD tools. To achieve that goal, the following steps were taken.
First, a Chicago office building with a typical facade system-single skin was designed as the base
case and it is described in detail in Chapter 6.
Then a numerical model was implemented to assess the energy performance of two typical DSF
systems (shaft and corridor type) and a naturally ventilated combined shaft-corridor DSF, (which
was a combination of the aforementioned ones) in comparison with the base case. In the next
stage, all the variable parameters were studied to optimize the DSF energy performance. Finally,
the results of the combined shaft-corridor DSF type with its variable parametric runs were
compared to optimize both energy and comfort performance.
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5.3 Developing inputs for the modeling process
The first step in the research procedure on energy performance of the combined shaft-corridor
DSF configuration is to collect climate-condition data and information on the building under
study which will be presented in detail in chapter 6. Chicago weather data was available through
the U.S. Department of Energy. EnergyPlus, the software that was used as the dynamic building
simulation, was also used that weather data for the energy analysis. These weather data includes
temperature, relative humidity (RH), wind, solar insolation. They are collected from a location at
Midway airport in Chicago which is close to the design site.
Figure 5.2 Chicago climate data
Figure 5.3 Wind rose
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The wind data for Chicago shows that the dominant wind flows through the south and west and it
is moving towards the North West.
5.4 Methodology for energy simulation and analyzing results
As suggested by Ternoey et al.(1985), the easiest way to evaluate energy improvements in
building design is to appraise energy use patterns with a base case. For this purpose, a typical
high-rise office building in Chicago was selected as a base case.
In this thesis, a parametric study was carried out focusing on energy use and thermal comfort.
The base-case office building with double low-E pane windows was simulated to calculate the
energy demand during the occupation stage. Then the same building with the combined shaft-
corridor DSF was simulated. Moreover, parameters such as cavity depth, air inlet size, exhaust
air opening size, as well as shaft height were all varied to study the impact of energy use and
thermal comfort on the building. This study is divided into three main parts:
• Development and simulation of the reference single-skin building
• Simulations of the combined shaft-corridor DSF in terms of energy and comfort
performance
• Simulation and analysis of the alternatives.
5.4.1 Simulation of the base case
After obtaining basic building and weather data, a simulation of the office building‘s energy
performance was undertaken. This was the base case simulation for a single skin facade system.
The simulation software used for this research was DesignBuilder with EnergyPlus as an engine.
It provides a user friendly interface, also 3D visualization and has the capacity to simulate energy
consumption from the basic input of the building shell, thermal zones, and climate data.
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5.4.1.1 Input for energy simulation tool
The first step was to choose the metric (SI international System) or IP (Inch-Pound) unit systems.
In order to build the model, the type of activity which is in this case is ―Office‖. Default building
parameters was chosen by selection of building use type. Then the geometry is built by importing
AutoCAD floor plans. DesignBuilder also follows a model data hierarchy.
This arrangement allows users to make settings at different levels. For instance, a selection of
wall type at the building level will affect all walls within the building while a selection at the
block level only affect the walls within the particular block.
In order to build the model, the window wall ratio and the construction of wall types can be
defined for all external and internal walls. Then based on information provided, the model can be
run to calculate the annual energy consumption hourly.
5.4.1.2 Output
After providing the inputs, the results will be generated as a detailed report of the heating/cooling
energies, peak and annual heating/cooling loads, and annual breakdown of energy consumption.
For this research, a major focus of the analysis is on the breakdown of energy consumption and
total annual cooling energy. It should be noted that the base-case energy consumption will be
compared with the new configuration as the goal of naturally ventilated DSF is to reduce the
cooling load by means of wind and natural convection.
Site Building Block Zone Surface Opening
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5.4.2 Generation of building alternatives
In this section, a description of the methodology of the parametric study is given. To study the
impact of design parameters on energy use and the thermal comfort performance of the
combined shaft-corridor DSF in comparison with the base case, different building alternatives
were simulated. The optimum alternative should facilitate the ventilation and be able to remove
hot air continuously from the cavity while optimizing energy efficiency.
Studying a naturally ventilated system is much more difficult than studying a mechanically
ventilated one, as the airflow rate depends on different parameters, such as the opening size,
glazing type, the geometry of the cavity, etc. For this reason, a further parametric study was
carried out for the naturally ventilated double-facade model to study the impact of parameters on
the system performance (see diagram 7.1):
• Influence of cavity height and depth on air temperature profile
• Influence of opening size on airflows and air temperature profile
• Influence of shaft size on airflow and air temperature profile
5.5 Computational Fluid Dynamics
The computational fluid dynamics (CFD) software, Fluent, was used to analyze the Thermal
performance of the combined shaft-corridor DSF cavity with wind and buoyancy-driven airflow.
Developing a CFD model for this case was a lengthy process and typically taking 72 hours for
each run. CFD has become a useful tool for designers in investigating the indoor environment
conditions in building designs. The parameters such as air velocity and air temperature solved by
CFD are critical for designing a comfortable environment. The application of Fluent in built
environment has been introduced in Chapter 4. In order to investigate the DSF design three steps
were taken:
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Step one: Establishing and assessing of the reference building.
Typical single skin facade office building (reference building) compared with two typical double
skin facade systems shaft and corridor types. To study the facade design‘s impact on the space
heating and cooling, a breakdown of energy components and overall energy consumption of a
typical office building is presented in chapter 6.
Step Two: Base case with Shaft-corridor DSF type assessment
To investigate the thermal performance of the combined shaft-corridor DSF, the boundary
conditions and domain needed to be established based on the climatic condition. The initial
simulation was concentrated on 7-story shaft height new configuration within a high-rise office
building. The office module is constructed using Gambit and Fluent software which described in
chapter 7 in details.
Instead of using the CFD software to model the whole high-rise building in one complete
computer model, the office building has been ‗divided‘ into several ‗blocks‘ vertically since the
height of the shaft is limited to a number of floors(7-story high for the first stage). Also just the
half of the block (division occurs horizontally) is modeled. The reason for the simplification is to
reduce the simulation time needed for each simulation run and any problem in the modeling
process or domain settings will be identified easier.
The high-rise office building can be ‗divided vertically‘ into four office blocks of 7-storey each.
One of the ‗office blocks‘ of 7-storey shaft height modeled with the similar boundary conditions
and simulations were runs to study the thermal comfort of the internal spaces. Results were
analyzed and details of the step-by-step modeling process were documented in Chapter 7.
Step three: Parametric runs
85
This level of simulation is to optimizing the Shaft-corridor DSF of double-skin facade (combined
shaft-corridor) which is presented in Chapter 8. The parameters used for the optimization are the
opening size, the shaft height and the cavity depth. These parameters are found to be most
important in affecting the facade system in providing optimum thermal comfort.
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Chapter 6.0
Energy Performance Assessment
6.1 Introduction
This chapter provides a detailed description of the reference building model as designed and used
for energy analysis in EnergyPlus- DesignBuilder. The building is modeled to assess the energy
performance of incorporating of three types of DSFs in comparison with the reference building.
A naturally ventilated combined shaft-corridor DSF and two typical corridor and shafts are
studied and compared with a single skin facade. The building is assumed to be in Chicago for
simulation and weather-data purposes.
To study the facade design‘s impact on the space heating and cooling, a breakdown of energy
components and overall energy consumption of a typical office building is presented.
First, the components of the reference building will be described. The next section discusses the
influence of different types of DSFs on space heating and cooling in comparison with the base
case office building. Finally, the results are compared with a traditional facade and with each
other in terms of energy performance and thermal condition.
6.2 Energy use in office buildings
In general, energy consumption in buildings is determined by function, climate, building
components, construction, control, and settings. The climate and the ambiance are considered as-
boundary conditions in energy simulation. Building function also has an important impact on
energy use. As shown in Chapter One, significant amounts of energy (50 percent) go into the
buildings and 23 percent of that goes into the office buildings. High occupancy and amounts of
equipment increase the energy consumption as compared with residential buildings. Building
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components and construction both provide great potential for improvement of energy demand in
such areas as adequate thermal insulation, a key component of energy consumption. In office
buildings, a careful choice of windows and shading devices should help to avoid additional solar
gains. Incorporating efficient HVAC equipment and heat recovery techniques may also reduce
the energy use. Designing a high-performance facade system will make a tremendous impact in
minimizing energy consumption and optimizing the thermal condition. To illustrate different
energy components in offices, Figure 6.1 presents a breakdown of a typical Chicago office
building. The results of this benchmark are presented in KW/ 𝑚2 𝑦𝑟 and based on a survey of a
large number of occupied office buildings. Typical patterns are representative for the median
energy use of 2003 office buildings.
Figure 6.1 Energy components of typical office buildings (US Department of Energy, 2003)
CASE Space
Heating Cooling Ventilation
Water
Heating Lighting Cooking Refrigeration
Office
Equip. Computers Other total
Typical 168.1 39.7 7.9 5.0 80.1 4.10 53.0 2.2 54.9 58.7 473.8
Best 103.5 28.1 16.4 6.3 72.9 0.9 9.1 8.2 28.4 19.2 293.1
Table 6.1 Energy components of typical and best practice office building in Chicago
0 100 200 300 400 500
Best
Ty
pic
al
kWh/m2
Energy End-Use Intensities for Office Buildings in
Chicago
Space Heating
Cooling
Ventilation
Water Heating
Lighting
Cooking
Refrigeration
Office Equipment
Computers
Other
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Space
Heating
44%
Cooling
12%
Ventilation
7%
Water
Heating
2%
Lighting
31%
Room
Electricity
4%
Best practice
Total energy consumption is split up into nine end uses and two energy resources (gas and
electricity). Gas is used for space heating and electricity consumption includes HVAC related
consumption (cooling, ventilation), and other building services (lighting, equipment, catering,
and water heating). In the Chicago climate, most of the energy goes into heating, as shown in the
pie chart below; as 36 percent of the typical office building‘s energy is for heating and 20
percent for cooling (there is no natural ventilation in typical office building).
Figure 6.2 Energy breakdown of a typical (right) and best-practice (left) building based on DOE surveys
In order to assess the impact of the DSF in this research, a reference building was constructed
and modeled. The results show that the model of reference building consumes 305.1
KWh/ 𝑚2 𝑦𝑟, which assumes that all traditional energy saving technologies are employed.
Therefore, in this study, the DSF impact is compared with the best-practice as the reference
building.
6.3 Description of the reference building
The description concerns the real (designed) building, and the simulated model created for the
energy and indoor-climate simulations.
The baseline facade configuration was a traditional, double glazed, low-E single skin facade.
Space
Heating
36%
Cooling
20%
Ventilation
2%
Water
Heating
1%
Lighting
17%
Room
Electricity
24%
Typical
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Initially, the reference building was a 28-story building as shown in Figure 6.3. It is a rectangular
shape with an open plan. In terms of geometry and installations, the floors are completely
identical. However, floors 1-27 are connected (floor, ceiling) with other internal building zones,
while the roof on the 28th floor is connected to the outside, and the ground floor is the ground
(i.e., no basement).
The height of the building is 98m, with a length of 78m, and a width of 32m. Architectural
drawings (floor plans, cross sections, facades) are presented in Appendix A. Room height is 3.5
m with a suspended ceiling. For this study, however, only part of the plan will be modeled both
in energy simulation and airflow modeling analysis. It was assumed that the building divided
into four blocks of 7-story high shaft modules. To simplify, the module to be studied is a
rectangle 28 m by 8.5 m. The module area is 229.5 𝑚2 and includes 7 stories, making a total of
1,607𝑚2. The window area (including the frames) comprises 100 percent of the south facade.
The interior design and the work places were not in the scope of the study. The four alternatives
based on external skin types were compared in terms of energy use and the quality of thermal
condition.
Figure 6.3 Left: View of the building in the site Right: Site Plan (Source: www.maps.google.com)
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6.3.1 Office layouts
Floor layouts for both single and double skin facade were designed with open plan offices and
shown in Figure 6.4. For the sake of simplicity, the simulation was created with as few thermal
zones as possible. Adiabatic conditions were assumed between the ceiling and floor on all floors,
which are identical zones, with similar temperatures.
Figure 6.4 Office Layout
The building‘s total floor area for the number of working places (only office rooms) is 15.4
𝑚2/occupant.
6.4 Simulation of single skin facade
After obtaining basic building and weather data, this
information was used to simulate the energy performance of
the single skin facade model.
Figure 6.5 View of the modled proportion of the single skin facade
in DesignBuilder
Module under
study 8.5m x 27m
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6.4.1 Input
First, the site needed to be chosen as illustrated in Figure 6.3. The site defines the building‘s
geographical location and weather data. Then the activity template, selected: open office space.
The occupancy schedules and other data, such as metabolic rates and levels of equipment use,
were set based on the office space requirements.
The occupants‘ schedules, activity levels, clothing and room use are shown in Table 6.2.
Schedule for offices 08:00 -12:00, 13:00 – 17:00
Winter schedule 50% working during the Christmas vacations, otherwise 100%
weekends closed
Summer schedule 75% working during July otherwise 100%,
weekends closed
Activity level Office Activity : 1 met = 108 W / occupant
(1 met corresponds to 58.2 W / 𝑚2 body surface)Task: sitting, reading
Clothing For winter conditions: 1 clo
For summer conditions: 0.6 clo
Table 6.2 Occupants schedule and activity level
6.4.1.1 Zone Identification
To simplify the simulation, only one zone per story was identified. The office building faces
south with 100 percent glazing.
6.4.1.2 Zone properties description
The two main components of the energy simulation model are the building fabric and elements
(walls, floors, ceilings, occupants, and equipment) and the plant components (HVAC equipment,
and other environmental control systems). Ventilation, lighting and equipment, type of HVAC
system, use of natural ventilation and daylighting should all be set in describing zone properties,
For all of these values, office-building defaults were used, except for the HVAC system, which
92
had a VAV system with terminal reheat that had been chosen for the base case. However, the
base case was simulated with no natural ventilation.
Then specific properties of each zone in terms of the wall properties (type, R-value, exposure,
and construction), shading, window properties (type, glazing area, size and layout) needed to be
set. The description of building‘s construction is shown in Table 6.2.
The glass area in the base case is 100 percent in the south facade and double-pane low-E
insulation was chosen for the glazing type.
Building
construction
Material type(from
outside to inside)
Thickness (m)
Density (kg𝑚−3)
U-value (W𝑚−2𝐾−1)
External wall Exposed concrete 0.10 1500
0.35 Polystyrene 0.08 16
Concrete block 0.10 1000
Gypsum plastering 0.013 758
Internal wall Gypsum Plaster 0.025 970
1.9232 Airgap 10mm 0.10 1.2
Gypsum Plaster 0.025 1090
Floor Cast concrete 0.10 2300 4.7
Ground floor UF Foam 0.087 1200
0.35 Cast concrete 0.10 2300
Creed 0.07 900
Wooden Flooring 0.03 1000
Roof Asphalt 0.01 930
0.25 MW Glass wool 0.145 16
Airgap 25mm 0.20 2.5
Plasterboard 0.013 720
Table 6.3 Description of building construction
The thermal properties of materials were initially calculated by EnergyPlus-DesignBuilder. It
should be noted that thermal losses due to thermal bridges were not included in these
calculations. In order to be accurate, practical values should be used instead of theoretical values.
93
6.4.1.3 Windows
The property of the reference window is as follows:
Window properties Description Aluminum window
U value (W/𝑚2𝐾) 4.719
Glazing properties Description Dbl LoE(e3=0.1) Clr 6mm/13Air
U value(W/𝑚2𝐾) 2.44
SHG 0.643
Frame properties Description Aluminum
Thickness 0.02
Surface resistance(𝑚2𝐾/W) 0.040
Shading device Description Blinds with high reflectivity slats
Control Scheduled and positioned inside
Table 6.4 Properties of window on south facade
6.4.1.4 Other settings
Control points for the indoor environment were set at 22 ℃ minimum for winter and 24.5 ℃ for
summer. The infiltration rate assumed for the reference building was 0.5 ACH (air changes per
hour). There were 300 occupants in the building. The lighting was assumed to be florescent with
a power of 10 W/𝑚2 200lux and the annual equipment energy use for the open plan was 57
kWh/𝑚2. Another parameter was a control set for artificial lights, assuming that they are
switched on according to occupant schedules.
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6.4.2 Output
6.4.2.1 Simulation results for the reference building
After the appropriate input to best define the typical office building was entered, the base case
was simulated for the year‘s annual performance. EnergyPlus generates a detailed report of the
heating/cooling energies, peak and annual cooling/heating loads, costs, and annual breakdown of
energy consumption.
For this thesis, only the most relevant output graphs were analyzed. The number of heating
degree days far exceeded the number of cooling degree days and clearly showed the heating-
season dominance. (Please refer to the detailed weather data for Chicago in the Appendix B). It
was apparent that due to the cold conditions, the most significant loads and maximum energy
use was for heating. In terms of breaking down annual energy consumption, the largest
components were space heating, cooling, and lighting. A building cost analysis was omitted, as
the major research objective was to study facades‘ thermal effects. The key point of adding a
naturally ventilated DSF was to take some of the grid‘s cooling loads out. Therefore, the major
focus of the analysis was on the following three output graphs:
a) Comfort
b) Annual Cooling and Heating Loads
c) Breakdown of Energy Consumption
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Figure 6.6 Fuel use break down of the reference building
Figure 6.7 Fuel breakdown of the simulated result with percentage of usage 274 total energy intensity
use
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
KW
hFuel Breakdown
DHW (Electricity) Chiller (Electricity) Heat Generation (Gas) System Pumps
System Fans Lighting Room Electricity
96
Figure 6.8 The reference building’s heating and cooling consumption
KWh Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Electricity 11,435 9,560 11,024 15,634 17,047 21,820 34,112 27,658 23,095 16,310 11,004 10,962
Gas 58,107 45,143 20,314 18,141 1,807 15 0 4 250 4,568 25,674 56,468
Table 6.5 Reference building simulation results, heating and cooling energy
6.5 Simulation of facade alternatives
6.5.1 Description of double skin facade alternatives
In this section, the energy performance of 7-story DSFs were studied and compared to the 7 story
section of the reference building. The energy demands of the following facades were studied:
A seven-story naturally ventilated cavity shaft type
A seven-story sealed outer skin-corridor type comprised of a single pane of clear glazing,
wherein the facade acts as an external air curtain
A seven-story naturally ventilated new DSF configuration combination of corridor and
shaft type.
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
80,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Gas
Electricity
97
Two DSF construction types were assumed: a corridor type and a shaft type. In both cases, the
cavity depth was assumed to be 1.5m and the shaft height was assumed to be 7 stories (3.5m
height). The main difference of the alternative facades is that a double skin has been added to
the building; with the internal skin the same as the reference building and the external skin as a
single pane window (6mm). The shadings were located inside the cavity. In both DSF types, the
building was mechanically ventilated, yet the cavity was naturally ventilated. The shading
devices were considered to be white with a slat angle of 45. Figure 6.9 shows these three
alternatives for energy simulation.
a: Base case facade b: Shaft type c: Corridor type
Figure 6.9 Diagram of the simulated double skin facades
The base case consists of a well insulating glazing with a U-value of 2.44 W/𝑚2𝐾 and a solar
transmittance of 0.634. The window is equipped with roller blind as shown in the Figure 6.9a. If
we added a clear glass pane (6mm) in front of the base case with divisions along each story that
allowed the exterior air to enter, the cavity a double skin facade corridor type is created (Figure
6.9-b). In the case of a shaft type, single glass was added to the exterior a small distance from the
insulated internal glazing, while the extracted air goes to a shaft that goes through multiple
stories and takes the exhaust air outside (Figure 6.9-c). The office was equipped with a
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mechanically ventilated system in case of variable weather condition and the natural airflow was
not enough to provide cooling.
Almost all the literature studies noted advantages regarding the reduction of heating/cooling
losses over traditional single facade systems. The lower radiant temperature increased building‘s
thermal comfort. Also, during the winter, the cavity can act as a buffer zone and capture incident
solar energy, which further improves the energy efficiency.
6.5.2 Combined shaft-corridor DSF
This study looks beyond typical shaft and corridor DSF solutions and provide a new type shaft-
corridor configuration. The combined shaft-corridor DSF configuration takes advantage of
strategies such as ventilation driven by different combinations of wind and external stack. The
most distinguishing visual feature of this configuration is it can pronounce a module by
projecting or taking back the towr on the facade as presented in Figure 6.10. This configuration
combined both shaft box and corridor types on the building‘s facade while trying to avoid their
disadvantages. The cooling stacks allow for further ventilation on hot, stagnant, summer days so
the building always remains within reasonable temperature levels, like that of an air-conditioned
building.
Figure 6.10 Sketch plan of the new configuration
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One of the disadvantages of a shaft-type window is that the narrow width makes it difficult to
clean and maintain. A corridor type can simply act as an internal or external air curtain. As a
result, natural wind cannot be introduced to the interior space; if we open the internal screen the
air inlet and exhaust air will mix. With the combined shaft-corridor DSF we tried to avoid the
disadvantages mentioned above. To avoid air mixing, the inlet and exhausted air are separated
through a channel. Exhausted office air will go directly into the transparent channel, which is
connected to the shaft. In addition, the shaft width is increased up to 1.5m, the same as the
corridor depth. Ventilation effectiveness is driven by thermal buoyancy, or stack effect, which is
determined by the inlet air temperature, the height between inlet and outlet openings, and size of
these openings.
Figure 6.11 shows how air flows through the chimney and provides ventilation inside each office
module. The air gap inlet draws in fresh air at a low level and directs it into the room. The air is
exhausted through the outlet at the high-level gap of the inner pane. The multi-story chimneys
sucks the exhausted air through a bypass opening at the top of the corridor facade. The vertical
height of the glass chimney creates a stronger uplift force due to the increased stack effect.
Figure 6.11 The combined shaft-corridor DSF configuration and show air flows within the building
100
6.5.3 Energy use simulation results
An annual energy simulation on an hourly basis under Chicago climatic conditions was
performed for different DSF alternatives. All inputs were the same as the reference building,
with the same floor area. In the case of the corridor facade, the width of the corridor was 1.5m
and the width of the shaft-type facade was 0.3m that passed through 7 stories. The energy
performances of the different DSFs will be discussed in detail in this section.
Figure 6.12 Energy breakdown in the combined shaft-corridor DSF configuration
The annual cooling and heating energy consumption of the combined shaft-corridor DSF is
presented in Figure 6.12. When heating and cooling loads were compared, it is apparent that
heating is the largest component of energy consumption. The heating season period is longer
than the cooling season in Chicago.
6.5.3.1 Energy demand results
The net annual gas consumption was reduced by 18 percent through the shaft, 16 percent through
the corridor type, and 35 percent in the new type (Shaft-corridor DSF). As shown in Figure 6.13,
the heating energy (gas consumption) was reduced in comparison with the two other typologies;
Room Electricity
23%
Lighting
7%
System
Fans
3%
System Pumps
7%
Heat Generation
(Gas)
37%
Chiller
(Electricity)
20%
DHW (Electricity)
3%
101
however, in terms of cooling demand, electricity consumption decreased by five percent in the
shaft type and nine percent in the corridor type. Total electricity was reduced by 15 percent in the
combined shaft-corridor DSF. Cooling and heating demands will be discussed in detail for each
month in the following section.
Figure 6.13 Annual gas and electricity demands
6.5.3.2 Cooling demand
It should be emphasized that the results represent the space heating and cooling energy demands.
Cooling efficiency differs from heating. The cooling demand is reduced each month in
comparison with the base case, except for the month of July, when it is lower than the shaft and
corridor types. However, the total annual cooling load was reduced by adding the DSF, as the
exterior shading devices decreased the heat solar gain, and made it easier to lose the indirect
solar gain. The results, consequences of the different climate, contradict Saelen‘s (2002)
findings. They also indicate that the combined shaft-corridor DSF increased the natural
ventilation even in hot summer months and would be a good option for the building.
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
Gas Electricity
KB
tu
Energy
Annual Energy Demand
Refernce
Shaft type
Corridor type
New type
102
Figure 6.14 Annual net cooling demand for each month
The Figure above shows the cooling demand of each month for the four different alternatives.
The total energy use for cooling has been reduced by 28 percent in the combined shaft-corridor
DSF and by almost five and seven percent in the shaft and corridor types, respectively. Based on
the energy simulation in Belgium by Saelens the south-oriented DSF requires 32 percent more
for cooling energy than the traditional facade (Saelens, 2002), while the combined shaft-corridor
DSF reduces cooling energy by 28 percent. Because of the extra pane, the DSF has a lower direct
solar gain, and the shading devices situated outside while in the base case the blinds located
inside which doesn't reduce the solar heat gain. In addition, with the combined shaft-corridor
DSF we can take advantage of both wind and natural convection that has occurred in the stack,
which improves the air velocity in eliminating the hot stuffy air from the building.
0
5,000
10,000
15,000
20,000
25,000
30,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
KW
h
Cooling Energy Demand
Base case
Corridor
Shaft Type
New Type
103
Figure 6.15 Cooling energy demand for four different enclosures
The total cooling energy is reduced by almost 28 percent, although this trend is not the same for
all the types in each month, as shown in the Figure above. The shaft and corridor types almost
save the same amount, however, the total annual reduction in the corridor type is seven percent
and five percent in the shaft type from the base case.
6.5.3.3 Heating demand
Comparing the DesignBuilder Heating and cooling demand for the four enclosures occurs in
Figure 6.16. The energy use for heating in the combined shaft-corridor DSF configuration is
several times lower than the base case demands and other DSF alternatives. In general, the
results seem to be remarkably different than the cooling savings and can be explained by the
following reasons: during the heating season the system would be closed thus no air is moving in
the cavity. The cavity then heats up and increases the temperature of the inner pane and thereby
reducing conductive, convective, and radiant losses. In addition, the whole system increases the
R-value of the enclosure by providing a buffer zone in front of the inner pane. The difference
between the maximum and minimum heating load is more pronounced than it was for the
0
5,000
10,000
15,000
20,000
25,000
30,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov
KW
hCooling Energy
Base case
Corridor
New Type
Shaft Type
104
cooling demand. It can be concluded that in the Chicago climate, the extra pane can lower the
heating load by 22 percent annually.
Figure 6.16 Heating energy demand for each month
6.5.3.4 Simulation results for the building
In this section, the energy-use difference for heating, cooling, and lighting is compared with the
three alternative facades and the base case. The energy use for heating in the reference building
is 34.7KWh/𝑚2 (25%) higher than the shaft and corridor types and 72 KWh/𝑚2 (50%) higher
than the combined shaft-corridor type, respectively. As expected, in all cases the energy use for
heating and cooling was higher than the reference building. However, Figure 6.17 shows
DesignBuilder results for lighting increased in the shaft and in the combined shaft-corridor DSF
in comparison with the base case by one percent. It can be concluded that 100 percent glazing
provides more daylight than the combined shaft-corridor DSF and shaft types, which makes
sense.
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
KW
h
Heating Energy Demand
Base case
Corridor
Shaft Type
New Type
105
Figure 6.17 Impact of facade types on energy use
Figure 6.18 Energy intensity of alternatives
The heating energy intensity was reduced by 50 percent in the new type (Shaft-corridor DSF)
and 28 percent in cooling energy intensity. In total, compared with the base case, the corridor
type reduced energy by 12 percent, shaft by 11 percent and the combined shaft-corridor DSF by
29 percent.
0 50 100 150 200 250 300
Basecase
Corrior
Shaft
New type
KWh/m2
Alt
ern
ati
ves
Room Electricity
Lighting
System Fans
System Pumps
Heat Generation (Gas)
Chiller (Electricity)
DHW (Electricity)
Base Case Corrior Shaft New type
Heating Demand 143.5 108.8 106.5 71.6
Cooling Demand 53.1 49.1 50.4 38.0
53.1 49.1 50.4 38.0
143.5
108.8 106.5
71.6
0
50
100
150
200
250
KW
h/m
2
Energy Intensity
106
Case Energy Intensity
KWh/𝑚2 yr Percent Savings (%)
Base 274.1
Corridor 239.3 12
Shaft 241.7 11
combined shaft-corridor 192.7 30
Table 6.6 Energy intensity of 4 cases and the percentage of savings
6.5.4 Impact of enclosure on the perception of thermal comfort
The section evaluates the indoor comfort of the different facade alternatives. The monthly
average values presented below are good indicators of the indoor thermal condition on
the building level, while the local discomfort is not in the scope of this study.
6.5.4.1 Average mean air temperatures
The mean air temperature difference between the new DSF type and the base case is very
small. As expected, the new configuration and other DSF alternatives provided a lower
temperature than the base case during the summer months, although they also reduced the
cooling loads. With strict temperature-set points for all alternatives, the PMV and PPD
values are quite similar, and just a few degrees lower than the base case.
Figure 6.19 Average mean temperatures for reference and alternatives
15
16
17
18
19
20
21
22
23
24
25
Jan
Feb
Mar
Ap
r
May Jun
Jul
Aug
Sep
Oct
No
v
Dec
Air
tem
per
atu
re F
Base case
Stack type
Corridor
New type
107
6.5.4.2 Perception of thermal comfort
The thermal comfort indices, PMV and PPD values, were calculated in DesignBuilder to
study the thermal comfort inside the office building. Since the building was assumed to
be the open plan type, average radiant temperatures of the external walls were calculated
and the occupants‘ position was not considered. The average PMV varied between -1 and
1 for the base case, slightly different for the Shaft-corridor type. The base case was
slightly hotter than the DSF alternatives and the new configuration was slightly colder
during the winter months than the base case and the other two DSFs. The single and
double skin enclosures performed similarly due to the strict temperature-set points.
Figure 6.20 PMV differences in four enclosures
The results in Figure 6.20 shows that during the winter months, the PMV results of Shaft-
corridor type is lower than the other types and the reason is that the cavity is not mechanically
heated and the sun space effect can not warm the cavity enough during the months December,
-2
-1.5
-1
-0.5
0
0.5
1
1.5
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
PM
V
Base case
Stack type
Corridor
New type
108
January, February. For climate of Chicago, the warm air needs to be introduced to the cavity
during these months to provide a better comfort for the occupants.
6.6 Summary of the energy use simulation results
The analysis of the basic DSF typologies shows their potential to lower the building‘s heating
demand. Heating energy consumption was higher than cooling energy consumption. The
reduction of energy losses and the possibility of providing a sunspace to take advantages of the
solar heat gain caused the combined shaft-corridor DSF and the other two DSF alternatives to
lower the heating needs more than the reference building.
In the Chicago climate, both heating and cooling loads were reduced simultaneously, which
contradicts with what Saelens (2002) found in Belgium for a south-oriented facade. Since the
exterior shading devices performed best during cooling season, the cooling demand was reduced
about 15 percent in the new configuration. The results indicate that natural ventilation of offices
is feasible in minimizing cooling energy and would be a good option in the summer time.
CASE Energy
Intensity KWh/𝑚2
Heating
Consumption KWh/𝑚2
Heating
Reduction
%
Cooling
Consumption KWh/𝑚2 yr
Cooling
Reduction
%
Reference building 274.1 143.5 53.0
Corridor type 239.3 108.8 24 49.2 7
Shaft type 241.7 106.6 25 50.5 5
Shaft-corridor type 192.7 71.6 50 37.9 28
Table 6.7 Summary of results
109
Chapter 7.0
CFD Modeling of the combined shaft-corridor DSF
7.1 Introduction
To preserve thermal comfort and reduce cooling loads, natural cooling strategies can be
incorporated into buildings. In this chapter, the behavior of natural ventilation in a new double
skin facade (DSF) configuration will be studied. To that end, Fluent, computational fluid
dynamics software (CFD), was used to study the office airflow path. Developing a CFD model is
a lengthy process. First, EnergyPlus-DesignBuilder was used to solve some boundary conditions,
such as solar thermal energy. Then a strategy was developed to reduce computation time, in
which half of the model was analyzed instead of running the whole model (the building is
symmetrical). The temperature profile and air velocity within the DSF‘s cavity and the internal
office space were simulated by Fluent, and, as a result, the offices‘ thermal comfort was
calculated and presented.
7.2 CFD modeling
Some researchers (Wong, 2008) argue that DSFs are the only means of natural ventilating in
buildings. In general, incorporating natural ventilation into high-rise buildings is prohibitive due
to high outdoor noise levels and/or high-wind speed levels. But under what conditions is
incorporation of natural ventilation possible with this combined shaft-corridor in a hot summer
continental climate? How are offices next to a DSF ventilated?
110
7.2.1 Climate data assumptions for the site
Simulations were performed with climatic data of Chicago (Midway airport). Weather data were
recorded by the World Meteorological Organization and includes 12 actual months. Natural
ventilation is possible during the shoulder season in Chicago. For this study, the months of May,
June, September, and October were explored.
Daily wind and hourly weather data is presented in the Figures7.1 through 7.4.
Figure 7.1 Weather data for May 14th, 2009, Chicago, Il
Figure 7.2 Weather date for June 14th, 2009, Chicago, Il
111
Figure 7.3 Weather data for Sep 16th, 2009, Chicago, Il
Figure 7.4 Weather data for Oct 15th, 2009, Chicago, Il
The first stage of the air flow modeling is to construct a simple model of the combined shaft-
corridor DSF configuration in Gambit (for detail information refer to Chapter 4). The numerical
model is three-dimensional and the model is based on a control volume method. The geometric
model of the entire building is constructed using a matrix of numbers to represent the points at
which surfaces meet.
112
In the next stage, the boundary conditions were solved, the grid size refined, and number of
necessary iterations determined. Fluent then generate a model that solved for wind velocity along
with buoyancy forces. The model used to solve the iteration was bousinesqe in order to consider
the buoyancy forces and in order to include wind force, the pressure at the surface boundary was
calculated (refer to Chapter 4 for more details). In order to define the external boundary
condition, the airflow needed to be solved for the external wind to be entered in Fluent.
7.2.2 External airflow modeling
In designing a naturally ventilated building, the site-condition effects such as adjacent buildings,
walls, and vegetation on wind velocity needs to be studied. One approach to study the external
airflow path is to build the building in its context in the CFD software. In this strategy, the
reference office building was modeled to analyze the wind pressure variable. The model was run
with a number of reference wind velocities to solve for air velocities near cavity openings. These
velocities could then be used as boundary conditions for a cavity model. The modeled wind
pressure around the building was used as a boundary condition for internal airflow modeling.
The image below shows the CFD model of the building located in the larger domain.
Figure 7.5 Wind distribution around the office at ground level (yellow: high wind speed, green: moderate
wind speed, and blue: low wind speed). The date of the simulation is May 1st
113
The surrounding buildings can either block or enhance wind speed around the site. The
computational domain for the building and its surroundings is shown in the Figure 7.5. The
domain length is about five times that of site length in four horizontal directions. The wind
distributions around the building were calculated for all directions with a typical wind speed for
each one. The grid number was too coarse so wind information was not sufficiently detailed.
Nevertheless, the results converged with a mass residual no higher than one percent.
In assessing wind effects on buildings, it is important to consider the characteristic wind nature
and the speed with height variability. The second approach to include the urban context effect on
airflow path is to solve the equation for specific airflow terrain. Vertical profiles of mean wind
speed for boundary layers are approximated by assuming the speed to be proportional to the
height raised to some power – a power-law variation (Davenport, 1965). The simple expression
used extensively has the following form:
Vh=aVmethb. (7.1)
Wind speed from the meteorological data corresponds to the speed at 10 m height in open
country. Since the building is located in an urban environment, the appropriate wind profile was
assumed to be (a=0.35 and b=0.25 are the constants which depends on the terrain in the vicinity
of the buildings),
Vh=0.35Vmeth0.25.
Where Vh is the local wind speed at height, h, and Vmet are the meteorological wind speed. Based
on this formula, wind has been calculated by Fluent for the specific times that the CFD analysis
was performed.
114
7.2.3 Wind pressure assessment
The wind-pressure distribution around a building depends very closely upon the local variation
in wind velocity that the building produces. In accordance with the elementary pressure-velocity
relationship, the pressure distribution is represented by a dimensionless pressure coefficient Cp:
Pw = Cp ρ Ur
2
2 . (7.2)
Where,
Pw= wind pressure, Pa
ρ = air density,kg
m3
Vr = wind speed at specified height, m s .
These formulas have been used to calculate the boundary conditions for the inlet pressure in
Fluent. This pressure plus static pressure is the total inlet pressure. There are default Cp values
provided in the airflow network-model simulation tools. These are based on the Air Infiltration
and Ventilation Centre‘s (AIVC) Guide to Energy Efficient Ventilation (Liddament, 1996),
which consists of a number of wind tunnel tests for generic, low-rise buildings. Typically, these
Cpvalues only apply as acceptable initial approximations for buildings that are close to
rectangularly shaped. The other approach to calculate more accurate pressure coefficients is to
analyze the external CFD analysis to provide the air velocity distributions and pressure around
the building due to wind effect. For simplicity, this investigation used an external CFD to
calculate the pressure difference as the boundary conditions for indoor airflow simulation. Wind
profiles one cell away from the building was recorded as inputs for the cavity model. These are
shown graphically in Figure 7.6, and values for x, y, z, and net velocities one cell away from the
building at the chimney entrance. These velocities are used as boundary conditions for a cavity
115
model, allowing for the analysis of cavities at any height. The results shown are for reference
velocities of 5 m/s and 10 m/s at 10 m above ground.
Figure 7.6 Velocity distribution around the building the prevailing wind, south at 5m/s
7.3 The geometry of the CFD model
The first stage of the internal CFD modeling is to construct a seven-story office module with
geometrical dimensions of 27x7 m, with 3.5 m ceiling height and 1.5 m cavity corridor in front
of the offices in the Gambit. The simplified single skin facade of the model has openings on
panes with 6mm thick glass. The DSF construction has one opening (inlet) at the outer pane and
two openings (air inlet and exhaust) at the inner pane. The model is constructed in 3-D in Gambit
as shown in the Figures 7.7, 7.8 and 7.9.
116
Figure 7.7 Vertical cross section of the combined shaft-corridor DSF
Figure 7.8 Three-dimensional grid model of the seven-story building with combined shaft-corridor DSF
configuration shown the gambit output
117
Figure 7.9 Model boundary settings
7.3.1 Model construction materials and components
The external walls of the office consisted of concrete with a density of 2,130 kg/𝑚3 and thermal
conductivity of 0.7 W/m-K. The outer pane of the DSF consists of single pane 6 mm clear glass,
and the inner pane, as described in Chapter 6, is a double pane low-E glazing. Simulations are
performed under steady state conditions using the k-epsilon turbulent model. Simulated wind
speeds are used to model expected wind velocities at the levels under study with corresponding
ambient and radiant temperatures shown later in this chapter. For this study, only wind direction
which is perpendicular to the DSF has been considered.
7.3.2 CFD model boundary conditions
This study is going to model levels from the sixteenth to the twenty-third stories of a high-rise
building. In the new configuration, the DSF has a ventilated shaft, which is 1.5x1.5 m with two
openings on the lower and high chimney levels. This study introduces a shaft to improve the
118
possibility of natural-ventilation stack effect to extract heat from the offices and improve airflow
rates required to reach thermal comfort level within the interior.
The results of Fluent model of this seven story block looked at the velocity profile, airflow
patterns, temperature within the double skin, and the internal office space. To calculate thermal
comfort, the boundary conditions for wind velocity, external temperature and relative humidity
were set to the ranges similar to Chicago climatic conditions and the inputs and assumptions are
presented in the Table 7.1.
Domain
Domain material Air at 20°C, 1 atm
Reference pressure 100,000 Pa (atmospheric pressure)
Reference temperature 295 K
Sources
Buoyancy model
Boussinesq-calculates airflow from temperature
difference rather than density difference.
Buoyancy reference temperature Outdoor air temperature.
Gravitational acceleration -9.81 m/s in the y-direction.
Boundary Conditions
Side, top, bottom, & front domain boundary
conditions
Openings with ―deduced‖ air velocities, external
temperature = outdoor air temperature at inflow
only, external pressure at atmospheric pressure.
Back boundary conditions Adiabatic solids (concrete) with depth = cavity
Depth, glass: standard 6 mm clear glass.
Heat source(external glass) 11.43 W/𝑚2
Heat source(internal glass) 7.93 W/𝑚2
Walls heat 25 W/𝑚2
Velocity inlet 5 m/s
Cavity Details
Cavity size 3.5 m high by 7 m wide by 1.5 deep.
Cavity external facade Internal plate with surface temperatures on both
sides is calculated based on heat source.
Table (cont.)
119
Cavity internal facade External plate with surface temperature base on heat
source.
Shaft and opening details
Shaft size 1.5 m deep,1.5 long, 24.5 m high
DSF opening size for inner pane, air gap size (inlet
and exhaust).
300 mm
Table 7.1 Model assumptions and inputs required by Fluent
7.4 Fluent simulation results demonstration
For the analysis of airflow and temperature in DSF and adjacent space, the base case with the
combined shaft-corridor DSF has been generated and airflow patterns and temperature profile
within the DSF has been illustrated for specific times of the year. Based on those data, the level
of thermal comfort within the space will be predicted. To study thermal comfort, the specific
internal space temperature and velocity at a particular height has been derived from the Fluent
analysis. The chimney opening size and inlets and outlets are 0.3 m; the chimney size is 1.5 m.
7.4.1 Cavity and room air temperature
The location of the chimney openings in this shaft-corridor type in relation to the chimney
exhaust will have an effect on the indoor thermal comfort and airflow velocity. It is a fact that
the higher the exhaust opening is located from the inlet, the stronger the stack effect will be
within the air gap. This effect will then pull more air from office spaces to circulate throughout
the building. The other factor that impacts on air velocity are inlet and outlet sizes. Due to the
venturi effect, the smaller the size, the more the velocity. Figure 7.10 illustrates the room‘s
temperature gradient, which is clearly lower than the outside temperature of 20 ˚C. There is some
temperature variation as the cavity is ventilated. The room air temperature increases towards the
top as shown in Figure 7.10.
120
Figure 7.10 As displayed in Fluent analysis of room temperature profile
Figure 7.11 clearly illustrates an increase in the gradient temperature from the inlet to the outlet
where higher-surface temperatures were reached due to accumulated heat and buoyancy effect.
Figure 7.11 Cavity temperature gradient
As illustrated in Figures 7.10 and 7.11, the interior air temperature is slightly higher than the
exterior in the half of the room closer to the cavity and also in the half upper part. The
121
temperature goes from 19 °C at the bottom opening to about 19.9 °C at the top opening. Figure
7.12 illustrates the temperature stratification from lowest on the floor to highest close to the
ceiling.
Figure 7.12 Cavity temperature profile-output from Fluent
Figure 7.12 also shows the cavity air temperature near the interior glazing. The temperature goes
from 18 °C at the bottom opening to about 19.5 °C at the top opening. The stack air temperature
increases towards the top of the chimney in a fairly linear progression, as shown by gradients in
Figure 7.13. Figures 7.10,7.11,7.12,and 7.13 depict the cavity model with 20° C outdoor air
temperature and 480 watts/𝑚2 incident solar energy obtained from the weather data. Figure 7.12
shows the interior air temperature is slightly higher than the lower half of the chimney air in
average 1°C per floor.
122
Figure 7.13 Chimney air temperature profile
Figure 7.14 shows a horizontal temperature profile at the level of 1 m from the floor (this is the
height of the body mass of a seated person). The air temperature varies in this direction from
about 20 ˚C near the glazing to about 19.3 ˚C in the center, and 18.5 ˚C in the back of the room.
The air reaches the higher temperature near the middle of the room, the point at which air
velocity is lowest. This Figure also illustrates how the concentration of heat is accumulated
mostly towards the center of the space.
Figure 7.14 The horizontal temperature profile of the room
123
A temperature contour study has shown that the office space‘s lower floors have lower internal
temperatures compared to the higher floors. As we increase the shaft height, the upper floors
would be hottest and probably uncomfortable for occupants during the summer month. It is
interesting to discover that the office‘s mid-portion floor areas for all the floors are having higher
temperatures when compared to the floor area of the front part. This could be due to the airflow
pattern shown in the next section.
7.4.2 Airflow
The air velocity through the cavity is due to buoyancy and wind forces, and it is quite high.
Figure 7.15 shows the building‘s air velocity model. The velocity in this model ranges from 7
m/s inlet to 2.3 m/s outlet of the chimney. The inflow from the external screen is 1 m/s and the
internal screen inflow velocity is 0.45 m/s, while the exhaust airflow is 0.46 m/s on average. The
exhaust air velocity to the chimney averages 1.3 m/s. The greatest velocity is near the inlet to the
chimney and exhaust from the stack. As shown in the Figure below, the velocities are increased
relative to the one-story high cavity.
Figure 7.15 Model of air velocity vector in the building
124
Figure 7.16 shows the section of airflow at the opening of one story horizontally. Velocities are
greatest near the opening, when the air is forced through the smaller area. In the back of the
room, air velocities are high as they move toward the exhaust to get out from the stack. As
illustrated in the Figure 7.15, air velocity in the chimney is higher close to the back wall of the
chimney, and it is generally laminar when driven only by buoyancy without wind effects.
Figure 7.16 Horizontal velocity profiles
Figure 7.17 Horizontal velocity gradient
125
Figure 7.17 shows the horizontal velocity profile in the cavity and chimney. The velocity ranges
from 0.46 m/s away from the surface and 0.97m/s near the opening. The variation from the
greatest to the least velocity magnitude are in the range of perception (0.1-1m/s) based on the
ASHRAE standard (2004).
The greatest velocities are near the cavity openings where the wind impacts the airflow rate.
Figure 7.18 shows velocity vectors at the openings of the chimney cavity model as analyzed in
Figure 7-1. Velocities are greatest near the openings, when air is forced through the smaller area.
In this model, the maximum velocity at the inlet is about 11 m/s. Other than at the openings,
airflow through the chimney well is around 5 m/s and is driven by both wind and stack effect.
Figure 7.18 Model of air velocity close to the inlet opening
126
Figure 7.19 Airflow patterns and velocity at the chimney’s outlet opening
A small turbulent flow forms at the stack inlet and outlet, and stack airflow is generally laminar
when it is only driven by buoyancy.
Figure 7.20 shows a vertical profile of air velocity vectors to the stack from the cavity. The
velocity is quite high and it extracts hot stuffy air from offices to the stack and outdoors. The
airflow is likely to be more effective in extracting heat when the wind velocity is high and the
temperature gradient occurs in the shaft increase the buoyancy effect.
127
Figure 7.20 Air velocity vectors in the cavity and chimney
Figure 7.20 shows how air comes inside the chimney, which is then extracted from the offices
through the chimney opening.
Figure 7.21 shows the section of air-flow path inside the cavity and shafts and how air from the
office outlet is directed outside. The air is basically induced to flow upwards by a buoyancy
effect created by the accumulated heat. Figure 7.21 illustrates how the flow reaches higher
velocities within the inlet and outlet where pressures are higher. As depicted, flow tends to be
turbulent near the glazed surfaces and openings where forces are higher. The airflow inside the
cavity is much higher than what is measured by typical examples in the literature.
128
Figure 7.21 Velocity vectors in the chimney and cavity
The airflow inside the room is illustrated in Figure 7.22. The Figure shows an air-movement
trend from laminar close to the wall boundaries to turbulent in the room‘s center. The airflow
inside the rooms is less than 1 m/s and more than 0.1 m/s.
Figure 7.22 Velocity vectors in the room
129
7.5 Analysis of the model solved by Fluent
k-e RNG Turbulence Model
Run Details Model Results
Model Grid number Run time iterations
∆T cavity
inlet and
exhaust
Airflow
rate(𝑚3
𝑟)
5,000,000 72 hours 1000 13.2 102.5
Table 7.2 The Fluent model information
Simulation Floor
Level
Temp.
C
Air
Velocity
Radiant
Temp
RH
%
PMV OT
May 3 20 0.28 22.53 40.7 0.18 20.22
5 22.4 0.16 22.93 47.3 0.29 20.3
7 24.8 0.11 23.64 45.59 0.37 20.56
June 3 23.7 0.20 27 51.1 0.5 20
5 24 0.19 27.50 50.68 0.66 21.30
7 24.6 0.15 28.19 56.60 0.76 21.09
Sep 3 23.4 0.27 26.3 50.3 0.4 24
5 23.7 0.20 26.25 57.40 0.54 25.38
7 24.2 0.13 26.98 56.35 0.71 25.20
Oct 3 22 0.27 23.3 36.4 -0.32 22
5 22.3 0.20 23.4 42.4 0.11 22.80
7 22.8 0.19 24.6 45.4 0.23 22.04
Table 7.3 Calculated air velocity in the office room: 0.5 meter from the windows and 1 meter from the
floor.
7.6 CFD result findings and analysis of the combined shaft-corridor DSF
The results for a south-facing, combined shaft-corridor DSF with external wind velocity of 5 m/s
and 50 percent air humidity, respectively, are tabulated in Tables 7.1. Results for the combined
shaft-corridor DSF type as shown in Figure 7.23 indicate that the DSF air gap size of 0.3m gives
a comfortable result for these particular conditions in a natural ventilated space.
The office space‘s lower floors would generate the lowest operative temperature due to the stack
effect provided by the DSF configuration. This has enhanced the natural ventilation strategy to
provide better internal thermal comfort condition.
130
There is an internal temperature difference of 1 ˚C for the DSF mid-floor, which could be due to
slower internal air velocity generated. The south-facing DSF configuration produced an 82
percent acceptability limit for the 0.3 m opening for external temperature 20℃, according to the
Thermal Environmental Conditions for Human Occupancy from ANSI/ASHRAE Standard 55-
2004.
Figure 7.23 Average PMV index first floor months under study
Figure 7.24 shows the distribution of PMV values calculated by DesignBuilder for the combined
shaft-corridor naturally ventilated DSF office spaces with values within 80 percent acceptable
limits. This distribution is for the third floor in May. For air velocity lower than 1m/s and a
temperature difference between radiant and ambient of lower than 4°K, the operative temperature
(𝑇𝑜𝑝 ) would need to be adjusted according to the formula 𝑇𝑜𝑝 =A𝑇𝑎 + (1-A) 𝑇𝑟 , where 𝑇𝑟 is the
ambient air temperature and 𝑇𝑟 is the radiant temperature.
V <0.2m/s 0.2-0.6m/s 0.6-1m/s
A 0.5 0.6 0.7
Table 7.4 Calculated air velocity in the office room: 0.5 meter from the windows and 1 meter from the
floor.
-0.4
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
May June Sep oct
PM
V i
nd
ex
Month
7-story shaft height
1.5m cavity depth, 0.3 opening
7 floors
131
Air movements determine convective heat and mass exchange of the human body with the
surrounding air. In the Chicago climate, high air velocities will increase the evaporation rate at
the skin surface, which results in a cooling sensation. The recommended upper limit of indoor air
movement is usually 0.8 m/s for human comfort; such air velocity permits the interior space to
be 1-2 degrees higher than the human comfort temperature to maintain desirable a comfort level
(Hien et al, 2005).
Figure 7.24 Average PMV as calculated in the room
It was found that the combined shaft-corridor DSF will generate a strong stack effect within the
air gap, which, in turn, will pull more air out from the office space through rear-wall vents. The
temperature generated within the office space is then desirable and close to the human comfort
requirement. The airflow pattern created will have a good ventilation effect with cool air coming
from the vents, and across and above the internal space, and discharge through the inner pane
high level opening.
7.7 Conclusion
The first stage of simulation of the combined shaft-corridor DSF was carried out on seven story
stack high to investigate the thermal behavior of this new design facade and evaluate the
132
processes involved in thermal comfort. This will become the base case for parametric studies in
chapter 8. Fluent was used to simulate turbulent airflow.
In order to verify the results, the precise approach of the CFD model depends on the the
boundary conditions-settings accuracy. Simulation of fluid dynamics based on natural
convection with air velocities requires extensive calculation time to get desired converged
residuals.
A process was also described to use pre-determined wind pressure values at the cavity‘s
openings to model a DSF cavity in a CFD model. This method reduces computation time that
would be needed to analyze wind effects along with buoyancy forces. CFD models were used to
determine velocities at various points on the reference building for wind velocity of 5 m/s based
on the weather data. These values can be implemented in models using the process described
earlier in this chapter.
Based on airflow modeling of the combined shaft-corridor DSF, it was found that the stack
encourages buoyancy and induces air movement. Convective forces inside the cavity could be
used to promote air extraction from the room, although it is needed to promote air movement
within the room to release the excess heat.
The CFD results appear to confirm the design's effectiveness in two ways. First, the airflow
follows the ceiling and exits through the chimney openings, which suggests that the cool night
air will effectively draw the heat out of the ceiling slab. The second outcome of the airflow
staying near the ceiling is the avoidance of high air velocities in the occupied zone during the
day. The main driving forces in the cavity are buoyancy and wind pressure. The pressure
differences resulting from these forces can be determined with the following equations:
∆𝑝𝑏𝑜𝑢𝑦𝑎𝑛𝑐𝑦 = 𝜌° ∗ 𝑔 ∗ 𝐻(𝑇𝑐𝑎𝑣
𝑇𝑒− 1)
133
where ρo is outdoor air density in kg/𝑚3, g is gravitational acceleration (9.8 m/𝑠2), H is the
cavity height in meters, Tcav is the average cavity temperature, and Te is the outdoor air
temperature in Kelvin. Thus,
∆𝑝𝑤𝑖𝑛𝑑 = 𝜌° 𝑈𝑚𝑒𝑡
2
𝑚𝑒𝑡 (
𝜕𝑚𝑒𝑡
𝑚𝑒𝑡)2𝑎𝑚𝑒𝑡 (2𝑎 − ( + 𝐻)2𝑎 ) (Pa)
Where Umet is measured wind speed at height hmet, δmet is the wind boundary-layer thickness,
a is the ASHRAE local terrain exponent, h is the height of the lower cavity opening, and H is the
distance between inlet and outlet openings. The airflow rate through the cavity can then be
determined with:
V = aΔpb (𝑚3/hr),
where a and b are pressure loss characteristics of the cavity and openings.
This chapter has shown that the combined shaft-corridor DSF has a possibility of providing
acceptable internal thermal comfort through natural ventilation strategy in a hot summer
continental climate. These results answered the first question posed in the introduction of this
chapter. The next chapter explores the parameters that can optimize the thermal condition and
energy performance of this new configuration for shoulder season.
134
Chapter 8.0
Parametric Optimization Studies of the Combined Shaft-corridor
DSF
8.1 Introduction
The energy analysis of the new DSF combined shaft-corridor configuration presented in the
previous chapters revealed that the new system is viable in terms of providing acceptable internal
thermal comfort through natural ventilation while also improving energy consumption. The
analysis was confined to a combined shaft-corridor DSF-system design that could provide the
significant extraction force required to ventilate the office spaces through combined wind and
buoyancy effects. In this chapter the results of systematically varying the base case are presented
to further investigate possibilities to improve the office airflow by modifying the new DSF
configuration system. The strategies include:
a) Modifying the ventilated stack by varying openings of the DSF system. Investigating different
sizes for openings and their effects on internal thermal comfort for office spaces and energy
performance. It should be noted that opening sizes are the same for the inlet, exhaust, and
chimney openings.
b) Varying the shaft height by extending the stack through a different number of stories to see
the effect on ventilation rates within internal office spaces.
c) Investigating the effect of cavity depth on airflow velocity.
e) Last, but not least, comparing the best performing alternatives in terms of energy and comfort.
135
8.2 Parameters examined
The modeling process described in Chapter 7 was used to analyze the performance of a number
of DSF cavity geometries with a range of variables. The main goals were to determine general
airflow and temperature profiles by varying the cavity geometry. In this analysis, the driving
forces for airflow are buoyancy and wind pressure based on the weather data in each of the
models. This allows for correlations to be developed for different parameters and can be used in
an annual DesignBuilder energy simulation.
Variables analyzed include:
Cavity Depth: 0.5 m, 0.9 m, 1.2 m and 1.5 m
Shaft height: 5 to 9 stories (3.5 m each story)
Opening Size: 0.3, 0.6 and 0.9m.
Figure 8.1 Parametric variables used in CFD.
Cavity
size
0.6-1.5
m
Opening to Shaft
136
Thirty-six different gambit models were developed to analyze the cavity geometry variables.
Each of the models was run in Fluent under a number of different environmental conditions to
determine trends in the cavity‘s airflow and temperature performance as described in the
previous chapter. All of the models are summarized in Table 8-1. Data from all of the runs are
included in Appendix D.
8.3 Parametric runs: Simulation results
Results from each of the thirty six fluent analyses provide values of indoor conditions for air
temperature, air velocity, and relative humidity were investigated at 1.2 m above floor level and
at the office space‘s center. Table 8.1 shows all alternatives taken from the simulations with
constant input conditions included an external temperature of 20 ° 𝐶, wind velocity of 5 m/s and
relative humidity of 52%.
Opening size
Cavity Height Parameters 0.3 0.6 0.9
1.5
m c
avit
y
7-story
Radiant Temp. 23.99 23.74 23.07
Velocity 0.3 0.3 0.35
RH 57.6 52.1 59.9
PMV 0.18 0.15 0.05
9-story
Radiant Temp. 23.94 23.75 23.07
Velocity 0.4 0.45 0.54
RH 57.6 59.73 52.31
PMV 0.18 0.15 0.11
5- story Radiant Temp.
23.55 23.76 23.76
Table cont.
137
Velocity 0.25 0.12 0.35
RH 57.39 52.99 52.53
PMV 0.18 0.15 0.15
1.2
m c
avit
y
7- story
Temperature 23.50 23.96 22.98
Velocity 0.35 0.44 65
RH 52.46 57.39 52.99
PMV 0.11 0.14 0.06
9- story
Temperature 23.45 23.92 22.94
Velocity 0.2 0.33 0.35
RH 52 52.46 58.78
PMV 0.1 0.1 0.02
5- story
Temperature 23.55 24 22.95
Velocity 0.45 0.47 0.57
RH 52.14 57.39 52.99
PMV 0.11 0.19 0.03
0.9
m c
avit
y
7- story
Temperature 23.63 23.72 23.73
Velocity 0.25 0.45 0.55
RH 52.46 48.78 53.14
PMV 0.12 0.14 0.06
9- story
Temperature 23.95 23.74 23.14
Velocity 0.45 0.6 0.55
RH 52.46 48.78 53.14
PMV 0.18 0.3 0.4
Table cont.
138
5- story
Temperature 23.81 23.74 23.2
Velocity 0.35 0.45 0.48
RH 54.15 54.17 55
PMV 0.15 0.46 0.06
0.5
m c
avit
y
7- story
Temperature 23.8 23.67 23.91
Velocity 0.3 0.3 0.4
RH 52.1 47.84 49.91
PMV 0.15 0.13 0.17
9- story
Temperature 23.77 22.52 22.85
Velocity 0.3 0.4 0.6
RH 50.65 52.99 52
PMV 0.15 0.18 0.16
5- story
Temperature 23.65 23.9 25.9
Velocity 0.5 0.3 0.35
RH 50.65 52.14 47.84
PMV 0.11 0.18 0.16
Table 8.1 Simulation results for different scenarios of the combined shaft-corridor DSF.
8.3.1 Impact of opening size on energy use and thermal comfort
In order to study the impact of the opening area on energy use, openings of 0.3, 0.6, and 0.9 m
(as described in Chapter 7, results were taken for May, June, Sep and Oct) were generated. A
cross-comparison diagram of energy use of these alternatives is presented in Figure 8.2. The
results show that cooling energy use for the 0.6 opening size is 9% and 15% for the 0.9 m
139
opening size, respectively, and decreased in comparison with the 7-story, 0.3 opening size as the
cavity depth remained constant. The heating load increased by 11 % for 0.6 and 27% for 0.9 m.
One of the main arguments for using increased opening areas in buildings is the provision of
better natural ventilation. However, the increased opening area leads to a reduction in energy use
for cooling but not for heating in the building. To make use of airflow more efficiently, attention
has to be paid to how the opening works with the chimney, which will be discussed in the next
section. In terms of energy use, the simulation shows that the best cases would be 0.3 m and 0.6
m opening sizes.
Figure 8.2 Impact of opening size on energy use
As previously stated, the perception of thermal comfort depends not only on the mean-air
temperatures, but also on the surface temperatures that surround the occupant. Thus, the opening
size is crucial for the perception of thermal comfort as it influences the airflow and radiant
temperature as seen in Figure 8.3. For the reference building, the monthly average PMV varies
from -0.3 to 0.5, while for the alternatives the monthly average PMV varies from -0.41 to 0.5 and
-0.55 to 0.36, respectively.
74.7
60.5
54.2
32.4
34.7
38.3
0 20 40 60 80 100 120
7floors1.5cavity0.9openig
7floors1.5cavity0.6opening
7floors1.5cavity0.3opening
KWh/m2
Heating load
Cooling load
140
Different opening sizes are tested to optimize energy and comfort for the combined shaft-
corridor DSF.
The findings show that an opening size of 0.6 provides optimum ventilation rates for the internal
office space and the most desirable thermal comfort conditions. In terms of energy consumption,
the 0.3 m opening reduces total consumption. Although a 0.3 opening size uses less energy, the
comfort levels of 0.9 and 0.6 m openings are better during the shoulder season. However, the
larger the opening sizes, the colder during the winter month. As illustrated in Figure 8.3,comfort
as shown by the PMV index is lower for the bigger opening size, which can be favorable during
warm months but not during the winter season.
Figure 8.3 Impact of opening size with shaft height (7-story), cavity depth (1.5 m) on comfort
For 7-story shaft height and 1.5 m cavity depth, the best case would be a 0.6 m-opening size.
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
May June Sep Oct
PM
V in
dex
Month
Impact of opening size
7floors1.5cavity
7floors1.5cavity0.9opening
7floors1.5cavity0.6opening
7floors1.5cavity0.3opening
141
Figure 8.4 Impact of opening size with 9-story shaft height, 1.5 m cavity depth on comfort
For Nine story shaft height and 1.5 m cavity depth the best scenario for the opening size would
be 0.9 m.
Figure 8.5 Impact of opening size with 5-story shaft height, 1.5 m cavity depth on comfort
But for a shorter shaft height, the variability of opening size from 0.6 m to 0.9m does not impact
much on the PMV.
As we reduce the shaft height and keep the cavity depth intact, the best case for an opening size
would be 0.6 m. As the shaft height decreased for the same cavity size, the smaller opening size
cannot provide the same thermal comfort for occupants.
Figure 8.6 shows the configurations of the CFD model for simulations under specific conditions.
-0.80
-0.60
-0.40
-0.20
0.00
0.20
0.40
0.60
May Jun Sep Oct
PM
V i
nd
ex
Month
Impact of opening size
9floors1.5cavity
9floors1.5cavity0.9opening
9floors1.5cavity0.6opening
9floors1.5cavity0.3opening
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
May June Sep Oct
PM
V i
nd
ex
Month
Impact of opening size
5floors,0.9cavity
5floors1.5cavity0.9opening
5floors1.5cavity0.6opening
5floors1.5cavity0.3opening
142
Graph 8.1 Temperature comparisons for different opening sizes (Shaft height: 7-story)
Graph 8.1 shows temperature comparisons for different opening sizes. The 0.9 m opening for the
bigger cavity depth shows lower indoor temperature, but as we reduce the cavity size (to 0.9m),
the opening has not impacted the operative temperature. As for a 0.5 m cavity, the temperature of
the 0.6 m opening increased in comparison with a 0.3m opening size, while the case 0.9 m cavity
depth the temperature has not changed much by increasing the opening size.
Figure 8.6 Airflow for different opening sizes (from right: 0.3m-0.6m-0.9m)
22.5
23
23.5
24
24.5
25
25.5
0.9 0.6 0.3
Tem
pera
ture C
Opening size
7floors0.5cavity
7floors0.9cavity
7floors1.2cavity
7floors1.5cavity
143
After taking all thermal comfort parameters into consideration, an opening of 0.3 m would
provide optimum results.
8.3.2 Impact of cavity depth on airflow, energy use, and thermal comfort
After establishing the optimum opening size for the combined shaft-corridor DSF, the second
parameter to investigate is the effect of different cavity depths on indoor thermal comfort and
energy use. Different cavity depth sizes of 0.5 m, 0.9 m, 1.2 m, and 1.5 m will be introduced to
the DSF system, with an optimum outer skin opening size of 0.6 m, and 0.3 m. It should be noted
that the inner pane and shaft exhaust openings are also equal to the outer skin opening size.
Figure 8.7 show simulation results for thermal comfort under the weather data presented in the
previous chapter. The results show that the optimum cavity sizes are between 0.9 and 1.2 m, as
presented in Figures 8.8, 8.9.
Figure 8.7 Impact of cavity depth on comfort with constant 7-story shaft height, 0.3m opening size
The research found that the optimum cavity width for maximizing the buoyancy-induced flow
rate was 0.5 m, as the height of the shaft remained 7-story. However, due to maintenance issues
for a 0.5 m cavity depth, the next optimum sizes would be 0.9 and 1.2 m. Research also found
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
May Jun Sep Oct
PM
V i
nd
ex
Month
Impact of Cavity Depth
7floors shaft height,0.3opening
7floors1.5cavity0.3opening
7floors1.2cavity0.3opening
7floors0.9cavity0.3opening
7floors0.5cavity0.3opening
144
that velocity rate in a DSF of a 7-story shaft height increased as cavity width increased from 0.5
m to 0.9 m but then the increase would be so small as the depth is increased further than 0.9.
Figure 8.8 Impact of cavity depth on comfort with constant 9-story shaft height, 0.3 m opening size
As we increase the shaft height with an 0.3 m opening size, the buoyancy flow rate will be
increased and lead to better thermal comfort as illustrated in Figure 8.9.
Figure 8.9 Impact of cavity depth on comfort with constant 5-story shaft height, 0.3 m opening size
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
May Jun Sep Oct
PM
V i
nd
ex
Month
Impact of Cavity Depth
9floors shaft height,0.3opening
9floors1.5cavity0.3opening
9floors1.2cavity0.3opening
9floors0.9cavity0.3opening
9floors0.5cavity0.3opening
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
May June Sep oct
PM
V i
nd
ex
Month
Impact of Cavity Depth
5floors shaft height,0.3opening
5floors1.5cavity0.3opening
5floors1.2cavity0.3opening
5floors0.9cavity0.3opening
5floors.5cavity0.3opening
145
It was expected that as the shaft height increased, the comfort level would be higher. However,
the results do not show much difference. This does not mean that air velocity has not increased
by adding to the shaft height. Air speed has increased but there are several other issues that
impact thermal comfort. The results in Figures 8.10 to 8.12 indicate a slightly better comfort
level in a 7-story shaft height with cavity depth of 1.2 m.
Figure 8.10 Impact of cavity depth on comfort with constant 7-story shaft height, 0.6 m opening
The results show better thermal comfort as opening size increased to 0.6 m -optimum opening
size- in comparison with 0.3 m. The cavity depth of 0.5 m shows better comfort with 0.6m
opening and the second best option would be 0.9 m with 0.3 m opening size.
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
May Jun Sep Oct
PM
V i
nd
ex
Month
Impact of Cavity Depth
7floors shaft height,0.6opening
7floors1.5cavity0.6opening
7floors1.2cavity0.6opening
7floors0.9cavity0.6opening
7floors0.5cavity0.6opening
146
Graph 8.2 Temperature comparisons for different cavity depth and shaft height
Comparing the operative temperature of different cavity depths shows that 1.2 m provides a
lower temperature and would be the optimum choice.
Graph 8.3 Temperature comparisons for different cavity depth and shaft height
In comparison of air temperature values shown in the graphs above for a 0.6 m opening, the
optimum cavity size would be 0.9 m and the results doesn‘t show much difference as the shaft
heights varied .
23.6
23.8
24
24.2
24.4
24.6
24.8
25
25.2
1.5 1.2 0.9 0.5
Tem
pera
ture C
Cavity Depth
5floors0.3opening
7floors0.3opening
9floors0.3opening
23.55
23.6
23.65
23.7
23.75
23.8
23.85
23.9
23.95
24
24.05
0.9 1.2 1.5
Tem
pera
ture C
Cavity Depth
5floors0.6opening
7floors0.6opening
9floors0.6opening
147
Figure 8.11 Impact of cavity depth on energy use
In terms of energy use the best case would be a 1.2 m cavity depth, which reduces the cooling
loads 13%, while a 10% reduction by introducing a 0.9 m cavity depth and 8 % reduction in a 0.5
m cavity depth, but in terms of heating energy use the best case is 1.5m cavity depth.
The findings show that a cavity depth of 1.2 m provides optimum ventilation rates for the
internal office space and the most desirable thermal comfort occupant conditions.
8.3.3 Impact of shaft height on energy use and thermal comfort
In order to investigate the shaft height on the combined shaft-corridor DSF, three different shaft
heights have been introduced to the system. Boundary conditions are the same as the reference
building in the previous chapter. The shaft height will be tested to provide the better thermal
comfort and energy use. At this stage, the shaft height will also be tested on the optimum
openings size and cavity depth obtained for the system in previous sections. The optimum
opening size for the outer pane is 0.3 m–0.6 m and the cavity depth size is set to
0.9–1.2 m.
0 20 40 60 80 100
7floors1.5cavity0.3opening
7floors1.2cavity0.3opening
7floor0.9cavity0.3opening
7floors0.5cavity0.3opening
KWh/m2
Heating load
Cooling load
148
Figure 8.12 Impact of shaft height on comfort with constant 1.5 m cavity depth, 0.3 m opening size
Figure 8.13 Impact of shaft height on comfort with constant 1.2 m cavity depth, 0.6 m opening size
It was found out the 7-story shaft height provides a slightly better comfort than the 9-story shaft
height. Although the air velocity will be increased in a 9-story shaft, the top floor would be
slightly warmer when the shaft height is increased more than 7 stories as illustrated in the graph
8.4.
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
May Jun Sep Oct
PM
V i
nd
ex
Month
Impact of Shaft Height
1.5m cavity depth, 0.3 opening
9 floors
7 floors
5 floors
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
0.4
0.5
0.6
May Jun Sep Oct
PM
V i
nd
ex
Impact of Shaft Height
1.2 cavity 0.6 opening
9 floors
7 floors
5 floors
149
The temperatrue graph of different shaft heights shows that the 1.2 m cavity size in the case of an
0.3 opening has a lower operative temperature in comparison with other depths. In the case of a
1.2 m cavity depth, the 9-story shaft high has a lower temperature than the 7-story high.
Graph 8.4 Temperature comparisons for different shaft height and cavity depth
It was found out that a 0.9 m cavity depth performed better when the opening size increased from
0.3 to 0.6 m. In the case of 0.9 m cavity depth and 0.6 opening size, the shaft height has not had
much impact on the temperature.
23.1
23.2
23.3
23.4
23.5
23.6
23.7
23.8
23.9
24
24.1
5 7 9
Tem
pera
ture C
Shaft Height
0.9cavity0.6opening
1.2cavity0.6opening
1.5cavity0.6opening
150
Figure 8.14 Impact of shaft height on energy use with 1.5 m cavity depth and 0.3 m opening size
Figure 8.15 Impact of shaft height on energy use with 1.2 m cavity depth and 0.3 opening size
After analyzing all simulation results and taking thermal comfort parameters into consideration,
a 9-story shaft high provides in average better comfort during naturally ventilated month but in
terms of energy, the 5-story shaft high performs better.
Both of graphs‘ energy and comfort analysis show that the 7-story shaft high is the optimum
solution and provides better indoor operative temperatures for offices spaces.
0 20 40 60 80 100 120
9 floors
7 floors
5 floors
KWh/m2
Impact of Shaft Height
1.5 cavity, 0.3 opening
Heating load
Cooling load
68.3
58.7
57.3
37.5
33.0
33.3
0 20 40 60 80 100 120
9 floors
7 floors
5 floors
Chart Impact of Shaft Height
1.2 cavity, 0.3 opening
Heating load
Cooling load
151
8.4 Double skin facade performance assessment
8.4.1 Comparison of the best comfort performance alternatives
In regards to the quality of indoor thermal comfort, it is evident that smaller opening areas
provide a more stable environment with fewer dissatisfied occupants. The percentage of
dissatisfied occupants increases mainly due to low inner surface temperatures during winter,
which is the result of bigger openings. When the monthly average PMV values for different
alternatives compared, the case with 9-story shaft height, 1.2m cavity depth, 0.9m-opening size
performs similarly with slightly lower PMV values than the case with 7-story shaft height, 1.2m
cavity depth and 0.9 m opening size. It can be concluded that for 1.2 m cavity depth with 0.9
opening, the shaft height does not impact thermal comfort.
Figure 8.16 Monthly average PMV for the different alternatives
In addition, the case of a 7- story shaft height 1.5 m cavity depth, 0.9 opening size performs the
same as 5 story shaft,1.2m cavity depth and 0.9 opening size and it can be concluded that
increasing two stories to the shaft height is similar to decreasing the cavity depth by 0.3 m.
-0.80
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8.4.2 Comparison of the best energy performance alternatives
8.4.2.1 Cooling season
During this period, heat needs to be extracted from the space to the cavity, and as the cavity
depth increases, the more heat can be extracted to the outside. Generally, solutions with larger
opening sizes and smaller cavity depths (models 0.9 m cavity depth) perform slightly better in
the Chicago climate. The larger opening size allows a greater airflow rate through the cavity,
thereby extracting more heat, and the smaller depth causes greater air velocities near the cavity
surfaces. In the case of a smaller cavity depth, the insolation helps extract heat because of a
greater buoyancy force. It is also notable that the taller shaft enhances the DSF performance. It
was expected that the taller shafts would result in more heat extraction and lead to lower
temperature but that is not always the case. Apparently the solar heat gain offset this to some
extent. However, the results in future show that a larger opening size would make these cavities
perform better.
The five-story high shaft performs well and it can be concluded that the solar heat gain trapped
in this type can be extracted more efficently with a large opening. This type of DSF is more
successful in extracting heat through the buoyancy effect.
8.4.2.2 Heating season
The DSF models that perform best in this season are those with the lowest airflow rate. This rate
can be due to smaller opening sizes or larger cavity depth. In these models, the solar heat gain
trapped within the cavity cannot be extracted from the stack. For instance By closely comparing
the energy performance of these two cases 5-story, 0.9 cavity, 0.3 m opening size, and 5-story
1.2 m cavity and 0.9 opening, it is notable that the larger the opening size the higher the heating
load.
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Figure 8.17 Energy use comparisons for different alternatives
The two cases of 7-story shaft height, 0.9m cavity depth and 0.6m opening size and 5-story shaft
height, 1.5m cavity depth and 0.9m opening size performs the best. In addition the case 7-story
shaft height 0.9m cavity depth and 0.3m opening size also would be an optimum choice. These
three alternatives are going to be investigated based on the
8.5 Comparison of the three optimum performance alternatives
Finally, a comparison of the best performing alternatives of energy use and thermal comfort has
been performed. An improved version of the reference single skin building was simulated.
The smaller area of windows and cavity depth resulted in a lower (compared with the rest of the
cases) heating and cooling demand, and the lowest total demand (91.7kWh/𝑚2a) occurred in a 5-
-story shaft, and 0.9 cavity, and 0.3 opening. The next two alternatives had the same shaft height
0
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Cooling load
Heating load
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but a larger opening size and cavity depth. For buildings with a larger opening area, the total
energy use increased by4 kWh/𝑚2a for the 0.6 m opening size, and by 10 a for the 0.9 m opening
size. Comparing the 7-story shaft height case, it was seen that a 0.9 cavity and 0.3 opening use
91.2 kWh/𝑚2a due to a decrease in the cooling demand. By taking into consideration both
energy and thermal comfort, the optimum cases were the 7-story shaft height with 1.2 cavity
depth and 0.6 opening size, or 7-story shaft height with 0.9 cavity depth and 0.3 opening size, or
5-story shaft height with 1.5 cavity and 0.3 opening size. The Case 7-story shaft height with 1.2
cavity depth and 0.6 opening size has the lowest cooling energy use and the case 5-story shaft
height with 1.5 cavity and 0.3 opening size has the lowest heating energy use.
Figure 8.18 Energy use of optimum alternatives
Figure 8.19 PMV index of optimum alternatives
58.7
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8.6 Optimization results and findings
After numerous attempts and comparisons to optimize DSF configurations to find acceptable
indoor thermal comfort conditions for office occupants, a number of positive findings were
observed. These results and findings will be of utmost importance as indications of whether this
new type of facade (Shaft-corridor DSF configuration) can be used as a mean to introduce
natural ventilation to high-rise buildings in a cold climate.
Optimization findings are summarized below:
a) The optimum opening size for the outer pane of the DSF system is 0.3–0.6 m.
b) The optimum air gap sizes for the DSF system with the optimum shaft height are between
0.9 m–1.2 m.
e) The optimum shaft height is 7-story and the thermal comfort of the upper floors is better than
the other cases.
The optimized DSF for Chicago climate is 7-story high shaft, 1.2m cavity depth, and 0.6m
opening size.
The parametric studies in optimizing the configurations of the DSF system have lead to the
construct of an improved DSF system for use in a cold climate.
Some of the important findings are tabulated below:
a) A DSF system with openings vs. cavity depth (shaft height constant).
As the opening size increased, the comfort improved with the same cavity depth.
In order to get the same results in thermal comfort, as the cavity depth is decreased, the opening
size should be increased.
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Figure 8.20 Opening size vs. cavity depth
b) A DSF system with opening size vs. shaft height (cavity depth constant).
Increasing the shaft height improved the thermal environment and as the shaft height increases
the opening size needs to increase to provide the same results.
Figure 8.21 Opening size vs. shaft height
c) DSF system cavity depth vs. shaft height (opening size constant).
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As the shaft height increases, the cavity depth should be decreased with a constant opening size
to provide the same results.
Figure 8.22 Cavity depth vs. shaft height
8.7 Summary and Conclusions
While there is a great deal of interest in transparent building in current architecture, larger areas
of glazing area results in higher building heating and cooling loads, and higher levels of energy
consumption. The advent of the double skin facade is a response to these problems. A DSF
provides the potential to introduce daylighting and natural ventilation to the building, resulting in
reduced energy consumption associated with those loads. In addition, a DSF could provide a
buffer zone between the outdoor and indoor environment, allowing it to act as a sunspace to
reduce the heating load. Annual energy savings of above 50% have been found.
In this research, the buoyancy and wind-driven energy flows through the cavity have been
analyzed with CFD.
A modeling process using CFD and EnergyPlus was developed to assess the performance of a
combined shaft-corridor DSF cavity that combines the shaft and corridor to take advantage of
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buoyancy-driven airflow. The model uses EnergyPlus to determine boundary conditions,
including glazing surface temperatures and heat flux, and CFD to analyze airflow rate and cavity
patterns in an iterative process. It was determined that a single iteration between the two models
provides sufficient convergence and accuracy. The combined shaft-corridor DSF strategy does
not yet have data from actual implementation from physical models. Construction of full scale or
reduced scale DSF structures has substantial capital requirements and considerable temporal
requirements for constructions and monitoring. The use of computer models and simulations can
provide an economical and efficient first assessment of the feasibility of a combined shaft-
corridor DSF strategy.
A process was also described to use pre-determined wind pressure values at the cavity‘s
openings to model a DSF cavity in a simpler CFD model than would otherwise be required. This
method reduces computation time that would be needed to model a cavity in a domain large
enough to analyze wind affects along with buoyancy forces. CFD models were used to determine
velocities at various points on a 10-story building for reference wind velocities of 5.0 and 10.0
m/s. These values can be implemented in models using the described process.
Simulations using the developed model were run for a number of different cavity configurations
in order to optimize the performance of this combined shaft-corridor DSF. The model was used
to develop correlations that describe a DSF cavity performance. Key correlations were also
described in the last section.
8.7.1 Energy performance assessment
In order to reduce energy use and improve indoor thermal environment, combined shaft-corridor
DSF were introduced. The combined shaft-corridor DSF is a system consisting of corridor and
shaft types. In this combined shaft-corridor DSF, chimneys are placed in such a way that air can
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flow through the intermediate cavity with no mixing of inlet and exhaust air. In principle, the
main purpose of the DSFs (as to energy use and thermal comfort) is to allow useful solar gains
into the building and to introduce natural ventilation during the shoulder season. This research
investigated the possibility of introducing natural ventilation and buoyancy in order to reduce the
cooling loads.
The distance between the skins in the parametric study was varied from 0.5 m up to 1.5 m. For
protection and heat extraction reasons, solar shading devices were placed inside the cavity. The
two driving forces, wind and buoyancy, were incorporated to enhance the building‘s ventilation.
A main requirement when designing ventilated DSF cavities is efficient heat extraction during
summer months. For naturally ventilated cavities, the key parameters are the characteristic height
of the cavity (height to depth ratio) and opening sizes. For naturally ventilated cases, the position
of a shading device inside the cavity has only a limited impact on the thermal comfort (Gen,
2003). Movable external louvers decrease cooling and the heating demands. The effect is
opposite for internally placed venetian blinds, resulting in the highest total energy use due to the
drastic increase in cooling demand. The location of shading devices in regards to the external or
internal screen was not in the scope of this study but a previous study shows that there is not
much impact on energy use (Afonso, 2003).
The energy savings achieved for this combined shaft-corridor DSF has been investigated by
changing those parameters to see how they can enhance the natural ventilation via buoyancy.
Regarding thermal comfort, the double facade alternatives performed slightly better due to the
higher (and closer to the 0 axis) PMV values during the swing months in comparison with the
reference combined shaft-corridor DSF. Introducing buoyancy and wind effect to the cavity
enhanced the airflow and results in lower cooling loads.
160
Often, increasing the opening size doesn‘t improve the energy performance of the DSF system.
Since as the larger openings reduces cooling loads, the heating loads increases respectively.
Finding the optimum opening size for each cavity is essential for improving the building‘s
thermal and energy performance, especially as with a bigger shaft depth and larger opening size
a building‘s energy use may vary substantially, depending upon the design. The external louvers
are located in the cavity with the same window properties. The difference in total energy use
between the reference combined shaft-corridor DSF (0.3 opening size, 1.5 m cavity, 7- story
shaft height) and the best performing alternative could be 158.8 kWh/𝑚2 𝑦𝑟. This is the same
alternative as the base case but the optimum opening size results in a reduction of energy by 10
kWh/𝑚2 𝑦𝑟.
8.7.2 Thermal comfort performance
The majority of this research focused on developing correlations that can be used to analyze the
energy performance of a DSF within an annual building energy simulation program. The most
notable finding is that a DSF cavity is successful in extracting more heat from the facade of a
building at an outdoor air temperature of 20 °C and insolation rates of 250 watts/𝑚 2more than a
single facade of equivalent insulating glazing. As a result, the thermal comfort level during the
shoulder season is within 80% acceptable. It was hypothesized that the combined shaft-corridor
DSF would show significant improvements in terms of enhancing the airflow and shading the
interior glazing. This is promising for the combined shaft-corridor DSF in its ability to reduce
cooling season loads by implementing natural ventilation to the interior.
Other conclusions:
• A 7-story cavity, with greater airflow rates from greater buoyancy-driven airflow, does not
show improved cooling season performance over a 5-story height cavity.
161
• The cavity models analyzed with larger opening sizes (0.9 m) and smaller cavity depths (0.5 m)
performed slightly better in the cooling season than the bigger cavity depth (0.9 m) and smaller
opening sizes (0.6 m). This is due to greater airflow rates with the larger opening size, and
slightly higher airflow velocities with a thinner cavity.
• The cavity depth has very little effect (from 0.9-1.5 m) on the airflow rate through the cavity;
the rate is largely driven by the cavity opening size with buoyancy-driven airflow.
• A closed cavity (buffer zone) in the heating season assumed in this study. The best performing
cavities in heating season have larger cavity depth to collect solar gain, and small opening sizes,
as expected.
Also, the correlations developed for airflow rate can also be used to make cavity design decisions
about depth and opening size. The equations will give a range of airflow rates from buoyancy-
driven and wind airflow from a given DSF cavity configuration.
Regarding the quality of the indoor environment, it is evident that the optimum opening size in
relation to shaft height and cavity depth areas provides a more stable environment, with fewer
dissatisfied occupants.
162
Chapter 9.0
Contribution and Future Works
9.1 Contribution
The building facade plays an important role in achieving the critical goals of thermal comfort
and energy efficiency. Due to technological advances, transparency, and the use of glass have
become an attractive option for building envelopes. Designing glass facades can provide outdoor
views, abundant natural light as well as the potential for natural ventilation. With the use of
glass, however, both heating and cooling loads increase due to heat loss during the cold season
and solar gain during the summer. The development of DSFs is one of the more promising
responses to this problem.
The combined shaft-corridor DSF incorporates natural ventilation between the interior and
exterior skin. It provides cooling by convective heat extraction and wind as a natural driving
force. It can provide a buffer zone between the indoor and outdoor air during heating season.
This dissertation proposed a new configuration of a DSF system by combining two typical
facade systems in hot summer continental climate. This can be used as a guideline in the initial
design of a DSF system in that context.
In literature, numerous studies have shown DSFs should work to improve energy efficiency
without calculation results or experiments (Arons and Glicksman, 2001) Gertis correctly points
out that few simulations have been made and few measurements are available to support the
benefits that have been claimed. Other researchers have provided models to simulate specific
DSF typologies but did not link the envelope-level results to the building energy performance.
Only a few combinations of building performance analysis and envelope performances are
163
available that were restricted to one typical configuration or one story building (Saelens, 2003).
Most studies on thermal performance of DSFs have been carried out in moderate climates and in
one-story buildings. Only one study (Hasse, 2006) has been done on refurbishing of buildings in
hot summer continental climates. My study departs from previous investigations in the following
aspects:
This study designed a new DSF configuration and coupled a dynamic energy simulation program
with airflow modeling of a control volume model. Further, it investigates the thermal
performance of a double skin facade in different configurations and in a different climate.
This research has bridged the gap of investigating a combined shaft-corridor DSF to provide and
improve natural ventilation in a high-rise office building in humid continental climate. The
research found that this Shaft-corridor DSF has advantages over the typical curtain wall system
in reducing the cooling load by allowing wind to be introduced as the driving force in
combination with the stack effect to enhance natural ventilation. This combined shaft-corridor
DSF combined a corridor facade and a shaft type as described in Chapter 2. The findings have
concluded that this Shaft-corridor DSF of facade system provides better thermal comfort in terms
of radiant temperature reduction and energy savings as much as 30 percent with a seven-story
shaft extension.
9.2 Limitation and recommendations for future work
Regarding the complexity of analyzing DSFs, a few assumptions have been made and limitations
are acknowledged. Following are some of the research areas that were not in the scope of this
study, which might be addressed in the future to reduce energy usage in high-rise buildings with
DSFs:
164
First, in addition to the whole building energy simulation, measurements on the actual model is
highly recommended. The results and findings from the research needed to be validated directly
with experimental results. This shortcoming could be overcome to some extend by installing full
size experimental model in Chicago climate and monitor the experimental results for a specific
period of time. Due to the time and cost constraints for the research, the simulation tools have
been used to study the different parameters in terms of energy savings and thermal comfort
analysis.
Second, the research has looked at overall comfort through different parameters such as air
temperature, air velocity, radiant temperature, relative humidity, and by calculating the PMV and
PPD to achieve indoor thermal comfort. Other issues associated with a DSF such as daylighting
and condensation, are not within the scope of this research. In addition, the local discomfort has
not been investigated within this research.
Third, this study has not looked at different internal partitions‘ positions. The internal airflow
patterns would be affected based on different layout spaces that can be investigated to point out
the stagnant points and thermal comfort conditions. In other words, the influence of geometrical
characteristics on airflows can be investigated and presented as a guideline for architects.
The next recommendation is to consider the integration of other technologies such as phase
change materials, PV, and aero gel transparent insulation to the DSF system. Some research has
been done in the integration of PV and DSF for low-rise buildings. However, further work need
to be done in humid continental climate for high-rise buildings.
Furthermore, it is necessary to investigate the energy life cycle and economic analysis, which are
the ultimate tools in assessing DSF impact on a global scale. Further, it is useful to identify the
165
importance of other parameters such as control strategies-dashboard system that may validate
and monitor the actual building performance.
Last but not least, the incorporation of nighttime ventilation to the DSF system has been
addressed in the literature. However, the impact of nighttime ventilation on the cooling loads has
not been investigated in this study.
9.3 Conclusion
This research has achieved the goals that were set out at the onset. The question of the viability
of naturally ventilated DSFs in high-rise buildings in a hot summer continental climate has been
answered.
In this unique type of DSF, there is no mixing of intake and exhausted air. Natural ventilation
strategies (wind and natural convection) could be enhanced to provide satisfactory indoor
thermal conditions for high-rise buildings in particular periods (shoulder seasons).
CFD as a feasible tool has been used to test the uncertainty in building design and the possibility
of solutions for a particular problem.
In order to reduce energy consumption and improve the indoor thermal environment of highly
glazed buildings, DSFs can be implemented for Chicago‘s climate.
During the parametric studies, the ventilation rate should be considered to estimate the inner
pane temperature. On one hand, reducing the heating demand is essential for office buildings
located in Chicago; on the other hand, sufficient ventilation results in efficient heat extraction
and low cooling demand.
In this study, i.e. detailed CFD calculations on a combined shaft-corridor DSF, the influence of
geometrical characteristics on airflows also was studied and a single case compared with the
166
combined shaft-corridor DSF. The obtained results presented as the energy performance of the
building and thermal comfort of occupants.
9.4 Final note
The development of new technology plays a major role in response to energy issues. To that end,
resources must be used wisely, while new ways of generating energy are being developed.
Consumption must be reduced and more types of renewable energies should be incorporated.
Technology and architecture should be integrated to face the challenge of the future. In the
worlds of the master architect of all time, Le Corbusier, ―The question of window hasn‘t been
solved yet.‖
167
References
Afonso, C., & Oliveira, A. (2000). Solar chimneys: Simulation and experiment. Energy and
Buildings, 32(1), 71-79.
Allocca, C., Chen, Q., & Glicksman, L. R. (2003). Design analysis of single-sided natural
ventilation. Energy & Buildings, 35(8), 785.
Allard, F. (1998). Natural ventilation in buildings - a design handbook . London, UK:
Earthscan Publications Ltd.
Al-Mumin, A. A. (2001). Suitability of sunken courtyards in the desert climate of Kuwait.
Energy and Buildings, 33(2), 103-111.
Alnaser, N. W., Flanagan, R., & Alnaser, W. E. (2008). Potential of making over to sustainable
buildings in the kingdom of Bahrain. Energy and Buildings, 40(7), 1304-1323.
Angus, H.H. & Associates Limited, Consulting Engineers. (2001). University of Toronto Centre
for Cellular and Biomedical Research: Draft Study of a Double Wall Facade.
Arens, E., Blyholder A. & Schiller, G. (1984). Predicting Thermal Comfort of People in
Naturally Ventilated Buildings. ASHRAE Transactions. Vol. 90, Pt. 1B, 1984, 12 pp.
Arons, D. (2000a). Properties and Applications of Double-Skin Building Facades. MSc thesis in
Building Technology, Massachusetts Institute of Technology (MIT), USA. Retrieved
from http://libraries.mit.edu/docs
Arons, D. M., & Glicksman, L. R. (2000b). Double Skin, Airflow Facades: Will the Popular
European Model Work in the USA? Proceedings of the ACE3 2000 summer study on
energy efficiency in buildings. New York.
ASHRAE Handbook of Engineering Fundamentals. (1993). American Society of Heating,
Refrigeration and Air Conditioning, Atlanta. pp. 336-338.
ASHRAE. (2001). ANSI/ASHRAE Standard 562-2001, Ventilation for Acceptable Indoor Air
Quality, Atlanta: American Society of Heating, Refrigerating, and Air-Conditioning
Engineers, Inc.
ASHRAE. (2004). ANSI/ASHRAE Standard 55-2004, Thermal Environmental Conditions for
Human Occupancy, Atlanta: American Society of Heating, Refrigerating, and Air-
Conditioning Engineers, Inc.
Awbi, H.B. (1991). Ventilation of Buildings, E &FN SPON.
168
Baldinelli, G. (2009). Double skin facades for warm climate regions: Analysis of a solution with
an integrated movable shading system. Building and Environment, 44(6), pp. 1107-1118.
Ballestini, G., Carli, M. D., Masiero, N., & Tombola, G. (2005). Possibilities and limitations of
natural ventilation in restored industrial archaeology buildings with a double-skin facade
in Mediterranean climates. Building and Environment, 40(7), 983-995.
Ballinger, J. A. (1988). The 5 star design rating system for thermally efficient, comfortable
housing in Australia. Energy and Buildings, 11(1-3), 65-72.
Balocco, C., & Colombari, M. (2006). Thermal behavior of interactive mechanically ventilated
double glazed facade: Non-dimensional analysis. Energy and Buildings, 38(1), 1-7.
Bartak, M., Dunovská, T., & Hensen, J. (2001). Design Support Simulations for a Double Skin
Facade. Proceedings of the 1st Int. Conf. on Renewable Energy in Buildings ―Sustainable
Buildings and Solar Energy 2001,‖ pp. 126-129, Brno, 15-16 November, Brno University
of Technology / Czech Academy of Sciences in Prague, Czech Republic. Retrieved from:
http://www.bwk.tue.nl/fago/hensen/publications/01_brno_dskin_design_support.pdf
Bartak, M., Beausoleil-Morrison, I., Clarke, J. A., Denev, J., Drkal, F., Lain, M., et al. (2002).
Integrating CFD and building simulation. Building and Environment, 37(8-9), 865-871.
Beausoleil-Morrison, I.( 2002). The adaptive conflation of computational fluid dynamics with
whole-building thermal simulation, Energy and Buildings, 34(9), 857-871.
Boake, T. M., Chatham, A., Harrison, K., & Lum, K. (2003). Doubling up II. Canadian
Architect, 48(8), 38-39.
Bouchet, B., & Fontoynont, M. (1996). Day-lighting of underground spaces: Design rules.
Energy and Buildings, 23(3), 293-298.
Burek, S. A. M., & Habeb, A. (2007). Air flow and thermal efficiency characteristics in solar
chimneys and trombe walls. Energy and Buildings, 39(2), 128-135.
Calderaro, V., & Agnoli, S. (2007). Passive heating and cooling strategies in an approaches of
retrofit in rome. Energy and Buildings, 39(8), 875-885.
Cen, X.-R., Zhan, J.-M., Yang, S.-C., Ma, Y. (2008). CFD simulation and optimization design of
double skin facade Zhongshan Daxue Xuebao/Acta Scientiarum Natralium Universitatis
Sunyatseni, 47 (SUPPL.2), pp. 18-21.
Cetiner, I., & Özkan, E. (2005). An approach for the evaluation of energy and cost efficiency of
glass facades.Energy & Buildings, 37(6), 673-684. doi:10.1016/j.enbuild.2004.10.007.
169
Champagne, C. (2002). Computational Fluid Dynamics and Double Skin Facades. Assignment
for the Architectural Engineering Computer Labs, Pennsylvania State University, USA.
Retrieved from: http://www.arche.psu.edu/courses/ae597J/Champage-Hw1.pdf
Chan, A.L.S., Chow, T.T., Fong, K.F., Lin, Z. (2009). Investigation on energy performance of
double skin facade in Hong Kong. Energy and Buildings, 41 (11), pp. 1135-1142.
Chandra, S., et al. (1986). Cooling with ventilation, Solar Energy Research Institute, Golden Co.
CIBSE- Chartered Institution of Building Services Engineers, . (1997).Natural
ventilation in non-domestic buildings. Chartered Institution of Building Services
Engineers.
Chow, W. K., Hung, W. Y., Gao, Y., Zou, G., & Dong, H. (2007). Experimental study on smoke
movement leading to glass damages in double-skinned facade. Construction and Building
Materials, 21(3), 556-566.
Chow, W. K., & Hung, W. Y. (2006). Effect of cavity depth on smoke spreading of double-skin
facade. Building and Environment, 41(7), 970-979.
Chow, W. K. (1996). Application of computational fluid dynamics in building services
engineering. Building and Environment, 31(5), 425-436.
Chou, S. K., Chua, K. J., & Ho, J. C. (2009). A study on the effects of double skin facades on the
energy management in buildings. Energy Conservation and Management, 50 (9): 2275-
2281.
Crespo, A.M.L. History of the Double Skin Facades. Retrieved from the web:
http://envelopes.cdi.harvard.edu/envelopes/content/resources/PDF/doubleskins.pdf
Daniels, Klaus. (1998) Low-tech light-tech high-tech : building in the information age Basel ;
Birkäuser
Davenport A.G. (1965). Proceedings of the conference on wind effects on buildings and
structures, vol 1. HMSO.
Dawson, L. (2005). Banking on Frankfurt. Architectural Review, 217(1299), 40-40.
De Dear, R. J., & Brager, G. S. (2002). Thermal comfort in naturally ventilated buildings:
Revisions to ASHRAE standard 55. Energy and Buildings, 34(6), 549-561.
Di Maio, F., & van Paassen, A.H.C. (2000). Second skin facade simulation with Simulink code.
International symposium air conditioning in high rise buildings (Shanghai).
Ding, W., Hasemi, Y., & Yamada, T. (2005). Natural ventilation performance of a double-skin
facade with a solar chimney. Energy & Buildings, 37(4), 411-418.
170
Djunaedy, E., Hensen, J.L.M., & Loomans, M.G.L.C. (2002). Towards a Strategy for Airflow
Simulation in Building Design Center for Building & Systems TNO - TU/e. Technische
Universiteit Eindhoven, the Netherlands. Retrieved from:
http://sts.bwk.tue.nl/erdj/papers/roomvent2002.pdf
Djuric, N., Novakovic, V., & Frydenlund, F. (2008). Heating system performance estimation
using optimization tool and BEMS data. Energy and Buildings, 40(8), 1367-1376.
Dorigati, R. (2005). Effetto urbano/New bayer HQ,leverkusen. L'Arca, (207), 2-11.
Duarte N, et al. (2001). An interferometric study of free convection at a window glazing with a
heated venetian blind. HVAC&R Research, 7(2):169–84.
Etheridge, D., Mat. (1996) Building ventilation: theory and measurement Chichester ; John
Wiley & Sons.
Faggembauu D., Costa M., Soria M., and and Oliva A.(2003). Numerical analysis of the thermal
behaviour of ventilated glazed facades in Mediterranean climates. Part I: development
and validation of a numerical model. Solar Energy. 75(3), 217-228.
Fanger, P.O. 1970. Thermal Comfort. Copenhagen: Danish Technical Press.
Farías, O., Jara, F., & Betancourt, R. (2008). Theoretical and experimental study of the natural
draft in chimneys of buildings for domestic gas appliances. Energy and Buildings, 40(5),
756-762.
Fluent 6.2 User‘s Guide. 2001. Fluent Inc.
Fuliotto, R., Cambuli, F., Mandas, N., Bacchin, N., Manara, G., Chen, Q. (2010). Experimental
and numerical analysis of heat transfer and airflow on an interactive building facade.
Energy and Buildings, 42 (1), pp. 23-28.
Gan, G. (1998). A parametric study of Trombe walls for passive cooling of buildings. Energy
and Buildings, 27(1), 37-43.
Gan, G. (1995). Numerical investigation of local thermal discomfort in offices with displacement
ventilation. Energy and Buildings, 23(2), 73-81.
Gavan, V., Woloszyn, M., Kuznik, F., Roux, J.-J. (2010). Experimental study of a mechanically
ventilated double-skin facade with Venetian sun-shading device: A full-scale
investigation in controlled environment. Solar Energy, 84(2), pp. 183-195.
Givoni, B. (1981). Conservation and the use of integrated-passive energy systems in architecture.
Energy and Buildings, 3(3), 213-227.
171
Givoni, Baruch. (1998) Climate considerations in building and urban design /New York : Van
Nostrand Reinhold.
Gosselin, J. R., & Chen, Q. (2008). A computational method for calculating heat transfer and
airflow through a dual-airflow window. Energy and Buildings, 40(4), 452-458.
Gratia, E., & De Herde, A. (2007a). Are energy consumptions decreased with the addition of a
double-skin? Energy and Buildings, 39(5), 605-619.
Gratia, E., & De Herde, A. (2007b). Greenhouse effect in double-skin facade. Energy and
Buildings, 39(2), 199-211.
Gratia, E., & De Herde, A. (2007c). Guidelines for improving natural daytime ventilation in an
office building with a double-skin facade. Solar Energy, 81(4), 435-448.
Gratia, E., & De Herde, A. (2007a). The most efficient position of shading devices in a double-
skin facade. Energy and Buildings, 39(3), 364-373.
Gratia, E. (2004a). Is day natural ventilation still possible in office buildings with a double-skin
facade? Building and Environment, 39(4), 399.
Gratia, E., & De Herde, A. (2004b). Natural cooling strategies efficiency in an office building
with a double-skin facade. Energy & Buildings, 36(11), 1139-1152.
Gratia, E., & De Herde, A. (2004c). Optimal operation of a south double-skin facade. Energy &
Buildings, 36(1), 41.
Gratia, E., and De Herde, A. (2004d). Natural ventilation in a double-skin facade. Energy and
Buildings, 36(2), 137-146
Haase, M., Amato, A. (2009). A study of the effectiveness of different control strategies in
double skin facades in warm and humid climates. Journal of Building Performance
Simulation, 2 (3), pp. 179-187.
Haase, M., da Silva, F. Marques and Amato, A. (2009). Simulation of ventilated facades in hot
and humid climates. Energy & Buildings, 41(4): 361-373
Haase, M., & Amato, A. (2008). Ventilated airflow windows for comfort in a hot and humid
climate. International Journal of Ventilation, 7(2), 113-124.
Haggag, M. A. (2007). Building skin and energy efficiency in a hot climate with particular
reference to Dubai, UAE. 1st International Conference on Energy and Sustainability,
ENERGY 2007, 105 (287-2970.
Hamza, N. (2008). Double versus single skin facades in hot arid areas. Energy and Buildings,
40(3), 240-248.
172
Hamza, N., & Underwood, C. (2005). ―CFD supported modeling of double skin facades in hot
arid climates‖, 9th
International IBPSA Conference Building Simulation 2005, Vol. 1,
Montreal (Canada). 365-372.
Hanby, V. I., Cook, M. J., Infield, D. G., Ji, Y., Loveday, D. L., Mei, L., et al. (2008). Nodal
network and CFD simulation of airflow and heat transfer in double skin facades with
blinds. Building Services Engineering Research and Technology, 29(1), 45-59.
Hasselaar, B. L. H. (2006). Climate adaptive skins: Towards the new energy-efficient facade. 1st
International Conference on the Management of Natural Resources, Sustainable
Development and Ecological Hazards, RAVAGE OF THE PLANET 2006, RAV06,
Bariloche. , 99 351-360.
Hensen, J. (2003). Paper Preparation Guide and Submission Instruction for Building Simulation
2003 Conference, Eindhoven, Netherlands.
Hensen, J., & Augenbroe, G. (2004). Performance simulation for better building design. Energy
and Buildings, 36(8), 735-736.
Hernandez, M. T. (2006). Cfd simulation of a double skin facade model [Short-term
Research Report].
Hien, W. N., Liping, W., Chandra, A. N., Pandey, A. R., & Xiaolin, W. (2005). Effects of double
glazed facade on energy consumption, thermal comfort and condensation for a typical
office building in Singapore. Energy & Buildings, 37(6), 563-572.
Hill, D. (2007). David Adjaye's MCA/Denver opens. Architectural Record, 195(12), 34-34.
Hoseggen, R., Wachenfeldt, B. J., & Hanssen, S. O. (2008). Building simulation as an assisting
tool in decision making. Case study: With or without a double-skin facade? Energy and
Buildings, 40(5), 821-827.
Huckemann, V., Kuchen, E., Leão, M., Leão, E.F.T.B. (2010). Empirical thermal comfort
evaluation of single and double skin facades. Building and Environment, 45(4), pp. 976-
982.
Janssens, A., & Hens, H. (2007). Effects of wind on the transmission heat loss in duo-pitched
insulated roofs: A field study. Energy and Buildings, 39(9), 1047-1054.
Jenkins, D., Liu, Y., & Peacock, A. D. (2008). Climatic and internal factors affecting future UK
office heating and cooling energy consumptions. Energy and Buildings, 40(5), 874-881.
Jiru, T. E., & Haghighat, F. (2008). Modeling ventilated double skin facade: A zonal approach.
Energy and Buildings, 40(8), 1567-1576.
173
Jones, J., & West, A. W. (2001). Natural ventilation and collaborative design. ASHRAE Journal,
43(11), 46-51.
Kaluarachchi, Y., Jones, K., James, P., Jentsch, M., Bahaj, A. S., Clements-Croome, B., et al.
(2005). Building facades: Sustainability, maintenance and refurbishment. Engineering
Sustainability, 158(2), 89-95.
Khan, N., Su, Y., & Riffat, S. B. (2008). A review on wind driven ventilation techniques. Energy
and Buildings, 40(8), 1586-1604.
Knowles, R. L. (2003). The solar envelope: Its meaning for energy and buildings. Energy and
Buildings, 35(1), 15-25.
Kuznik, F., & Rusaouen, G. (2007). Numerical prediction of natural convection occurring in
building components: A double-population lattice Boltzmann method. Numerical Heat
Transfer; Part A: Applications, 52(4), 315-335.
Lechner, N. (2009). Heating, cooling, lighting: design methods for architects .
Hoboken, New jersey: Wiley.
Li, D. H. W., & Lam, J. C. (2000). Solar heat gain factors and the implications to building
designs in subtropical regions. Energy and Buildings, 32(1), 47-55.
Liddament, MW. (1992). The role and application of ventilation effectiveness in design.
Proceedings of International Symposium on Room Air Convection and Ventilation
Effectiveness, University of Tokyo, 59-75.
Lou, W., Li, H., Wei, K., Chen, Y., & Li, H. (2008). Wind tunnel test study on wind pressure
distribution on double-skin facades of high-rise buildings with typical shapes. Harbin
Gongye Daxue Xuebao/Journal of Harbin Institute of Technology, 40(2), 296-301.
Lou, W., Hu, W., Wang, W. (2009). Numerical analyses for scale effect on wind pressure of
double-skin facades and its mechanism. Tongji Daxue Xuebao/Journal of Tongji
University, 37 (10), pp. 1291-1295+1301.
Manz, H., & Frank, T. (2005). Thermal simulation of buildings with double-skin facades. Energy
& Buildings, 37(11), 1114-1121.
Manz, H. (2003). Numerical simulation of heat transfer by natural convection in cavities of
facade elements. Energy & Buildings, 35(3), 305.
Marques da Silva, F., & Gloria Gomes, M. (2008). Gap inner pressures in multi-story double
skin facades. Energy and Buildings, 40(8), 1553-1559.
Masoso, O. T., & Grobler, L. J. (2010). The dark side of occupants‘ behavior on building energy
use. Energy and Buildings, 42(2), 173-177.
174
Menezo, C., Fossa, M., & Leonardi, E. (2007). An experimental investigation of free cooling by
natural convection of vertical surfaces for building integrated photovoltaic (BIPV)
applications. 1st International Conference on Thermal Issues in Emerging Technologies,
Theory and Applications; Proceedings - ThETA1, Cairo. 125-131.
Mitchell, J.W., Beckman, W.A. (1995). Instructions for IBPSA Manuscripts, SEL, University of
Wisconsin, Madison, WI.
Murakami, S. 1992. New scales for ventilation efficiency and their application based on
numerical simulation of room airflow, In: Proceedings of International Symposium on
Room Air Convection and Ventilation Effectiveness, University of Tokyo, 22-38.
Navvab, M. (2005). Full scale testing and computer simulation of a double skin facade building.
9th
International IBPSA Conference Building Simulation 2005, Vol 2, Montreal
(Canada). 831-838.
Navvab, M., Varodompum, J., & Arch, M. (2006). Thermal performance of a double skin facade
using full scale testing, computer simulation and actual building. ASME International
Solar Energy Conference - Solar Engineering 2006, Denver, CO.
Orme, M.(1999). Applicable Models for Air Infiltration and Ventilation Calculations, AIVC
Technical Reports.
Oesterle, E., Leib, R.D., Lutz, G., Heusler, B. (2001). Double skin facades: integrated planning:
building physics, construction, aerophysics, air-conditioning, economic viability, Prestel,
Munich.
Osanyintola, O. F., Talukdar, P., & Simonson, C. J. (2006). Effect of initial conditions, boundary
conditions and thickness on the moisture buffering capacity of spruce plywood. Energy
and Buildings, 38(10), 1283-1292.
Pappas, A., Zhai, Z. (2008). Numerical investigation on thermal performance and correlations of
double skin facade with buoyancy-driven airflow Energy and Buildings, 40 (4), pp. 466-
475.
Park, C., Augenbroe, G., Sadegh, N., Thitisawat, M., & Messadi, T. (2004). Real-time
optimization of a double-skin facade based on lumped modeling and occupant preference.
Building and Environment, 39(8), 939-948.
Park, C., Augenbroe, G., Messadi, T., Thitisawat, M., & Sadegh, N. (2004). Calibration of a
lumped simulation model for double-skin facade systems. Energy & Buildings, 36(11),
1117-1130.
Pasquay, T. (2004). Natural ventilation in high-rise buildings with double facades, saving or
waste of energy. Energy and Buildings, 36(4), 381-389.
175
Platt, G., Li, J., Li, R., Poulton, G., James, G., & Wall, J. (2010). Adaptive HVAC zone
modeling for sustainable buildings. Energy and Buildings, 42(4), 412-421.
Poirazis, H. (2004). Double Skin Facades for Office Buildings: Literature review, Report EBD-
R-04/3, Department of Construction and Architecture, Lund University.
Radhi, H. (2008). A systematic methodology for optimizing the energy performance of buildings
in Bahrain. Energy and Buildings, 40(7), 1297-1303.
Rey, E. (2004). Office building retrofitting strategies: Multicriteria approach of an architectural
and technical issue. Energy & Buildings, 36(4), 367.
Rijal, H. B., Tuohy, P., Humphreys, M. A., Nicol, J. F., Samuel, A., & Clarke, J. (2007). Using
results from field surveys to predict the effect of open windows on thermal comfort and
energy use in buildings. Energy and Buildings, 39(7), 823-836.
Roth, K., Lawrence, T., Brodrick, J. (2007). Double-skin facades. ASHRAE Journal, 49 (10), pp.
70-73.
Saelens, D., Roels, S., & Hens, H. (2008). Strategies to improve the energy performance of
multiple-skin facades. Building and Environment, 43(4), 638-650.
Saelens, D., Carmeliet, J., & Hens, H. (2003). Energy performance assessment of multiple skin
facades. International Journal of HVAC&R Research 9 (2): 167-186. Retrieved from:
http://www.bwk.kuleuven.ac.be/bwf/pdf_artikels/I_J_HVACR_DS_2003.pdf
Saelens, D. (2002). Energy Performance Assessments of Single Storey Multiple-Skin Facades.
PhD thesis, Laboratory for Building Physics, Department of Civil Engineering, Catholic
University of Leuven, Belgium. Retrieved from:
http://envelopes.cdi.harvard.edu/envelopes/content/resources/pdf/case_studies/PhD_Dirk
_Saelens.pdf
Saelens, D., & Hens, H. (2001). Experimental evaluation of airflow in naturally ventilated active
envelopes. Journal of Thermal Envelope and Building Science, 25(2), 101-127.
Saelens, D., Carmeliet, J., & Hens, H. (2001). Modeling of Air and Heat Transport in Active
Envelopes, Proceedings of ICBEST 2001, International Conference on Building
Envelope Systems and technologies, Ottawa, Canada, pp. 243-247.
Safer, N., Woloszyn M., Roux J.J., Kuznik F. (2005). Modeling of the double skin facades for
building energy simulation: radiative and convective heat transfers. 9th
International
IBPSA Conference Building Simulation 2005, Vol. 2, Montreal (Canada). 1067-1074.
Santamouris, M. (2007). Advances in building energy research. London Sterling VA: Earthscan.
176
Scartezzini, J. (2004). Foreword. Energy and Buildings, 36(4), 319-320.
Shang-Shiou L. (2001). A Protocol to Determine the Performance of South Facing Double Glass
Facade System A Preliminary Study of Active/Passive Double Glass Facade Systems,
master thesis, Virginia Polytechnic Institute and State University.
Stec, W. J., & Paassen, A. H. C. v. (2005). Symbiosis of the double skin facade with the HVAC
system. Energy & Buildings, 37(5), 461-469.
Stec, W.J., Van Paassen, A.H.C., Maziarz, A. (2005). Modeling the double skin facade with
plants. Energy and Buildings, 37(5), pp. 419-427.
Stec, W., & Passen D. (2003). Defining the performance of the double skin facade with the use
of the simulation model. 8th
International IBPSA Conference Building Simulation 2003,
Vol 2, Eindhoven (Netherlands). 1243-1250.
Stec, W., & van Paassen, D. (2003). Integration of the double skin facade with the buildings.
674-681.
Straube, J. F., & Straaten, R.V. (2002). The technical Merit of Double Skin Facades for office
Buildings in cool humid climates. School of Architecture, University of Waterloo, USA.
Retrieved from: http://www.civil.uwaterloo.ca/beg/Downloads/DoubleFacadesPaper.pdf
Subject index of volume 37. (2005). Energy and Buildings, 37(12), 1292-1304.
Subject index of volume 38, (2006). Energy and Buildings, 38(12), 1495-1509.
Suma, A. B., Van Herwijnen, F., & Voorthuis, J. C. T. (2007). 3D adaptable building skin:
Adaptive space as a guide through a corridor. International Journal of Space Structures,
22(3), 169-177.
Supic, P. (1982). Vernacular architecture: A lesson of the past for the future. Energy and
Buildings, 5(1), 43-54.
Szokolay, S. V. S. V. (1980). Environmental science handbook for architects and builders,
Construction Press, Lancaster.
Szucs, E. (1980). Similitude and Modeling. Amsterdam, Netherlands: Elsevier Scientific
Publishing Co.
Tanaka, H., Okumiya, M., Tanaka, H., Young Yoon, G., Watanabe, K. (2009). Thermal
characteristics of a double-glazed external wall system with roll screen in cooling season.
Building and Environment, 44(7), pp. 1509-1516.
Ternoey, S. and Bicle L., Robbins C., Busch R., and McCord, K.(1985). The design of energy
responsive commercial buildings. New York: Wiley &Sons.
177
Todorovic, B., & Maric, B. The influence of double facades on building heat losses and cooling
loads. Faculty of Mechanical Engineering, Belgrade University, Belgrade, Yugoslavia.
Torres, M., Alavedra P., Guzman A., 2007, ―Double skin facades-cavity and exterior openings
dimensions for saving energy in a Mediterranean climate.‖ IBPSA Proceedings of
Building Simulation 2007, 198-205.
Turner, F. (2009). Air tightness in buildings. ASHRAE Journal, 51(4), 5. Retrieved from
Academic Search Premier database.
Von Grabe, J. (2002). A prediction tool for the temperature field of double facades. Energy &
Buildings, 34(9), 891.
Wei, J., Zhao, J., & Chen, Q. (2010). Energy performance of a dual airflow window under
different climates. Energy and Buildings, 42(1), 111-122.
Wenting Ding, & Hasemi, Y. (2006). Smoke control through a double-skin facade used for
natural ventilation. ASHRAE Transactions, 112(1), 181-188.
Wigginton, M. (1996). Glass in architecture, Phaidon Press, London, England.
Wigginton, M. (2002). Intelligent skins, Butterworth-Heinemann, Oxford.
Wittkower, W. J. (1984). Climate-adapted building in Israel: How far has our knowledge
influenced building practice? Energy and Buildings, 7(3), 269-280.
Wong, P.C., Prasad, D., Behnia, M. (2008). A new type of double-skin facade configuration for
the hot and humid climate. Energy and Buildings, 40(10), pp. 1941-1945.
Xamán, J., Álvarez, G., Lira, L., & Estrada, C. (2005). Numerical study of heat transfer by
laminar and turbulent natural convection in tall cavities of facade elements. Energy &
Buildings, 37(7), 787-794.
Xu, X., & Yang, Z. (2008). Natural ventilation in the double skin facade with venetian blind.
Energy and Buildings, 40(8), 1498-1504.
Yellamraju, V. (2004). Evaluation and design of double-skin facades for office
buildings in hot climates (Master‘s thesis), Available from Dissertations and Theses
database at Texas A&M University.
Yılmaz, Z., & Çetintaş, F. (2005). Double skin facade's effects on heat losses of office buildings
in istanbul. Energy & Buildings, 37(7), 691-697.
Zerefos, S. C. (2007). On the performance of double skin facades in different environmental
conditions. International Journal of Sustainable Energy, 26(4), 221-229.
178
Zhang, M., Lou, W., & Chen, Y. (2008). Wind pressure distribution and gust factor on double-
skin facades of high-rise building with rectangular shape. Zhejiang Daxue Xuebao
(Gongxue Ban)/Journal of Zhejiang University (Engineering Science), 42(1), 54-59.
Zhou, J., Chen, Y. (2010). A review on applying ventilated double-skin facade to buildings in
hot-summer and cold-winter zone in China. Renewable and Sustainable Energy Reviews,
14 (4), pp. 1321-1328.
Zhou, J., Chen, Y.-M., Fang, S.-S. (2009). Ventilated double skin facades in hot-summer and
cold-winter zones in China Hunan Daxue Xuebao/Journal of Hunan University Natural
Sciences, 36 (SUPPL.), pp. 160-162.
Zöllner, A., Winter, E. R. F., & Viskanta, R. (2002). Experimental studies of combined heat
transfer in turbulent mixed convection fluid flows in double-skin-facades. International
Journal of Heat and Mass Transfer, 45(22), 4401-4408.
Zrudlo, L. R. (1988). A climatic approach to town planning in the arctic. Energy and Buildings,
11(1-3), 41-63.
179
APPENDIX A: Drawings
Plan of the office building designed in Chicago
Section of new DSF
180
Elevation view of the shaft-corridor DSF configuration of office building
181
APPENDIX B: Weather data
Statistics for USA_IL_Chicago-Midway.AP.725340_TMY3
Location -- Chicago Midway Ap IL USA
{N 41° 46'} {W 87° 45'} {GMT -6.0 Hours}
Elevation -- 186m above sea level
Standard Pressure at Elevation -- 99110Pa
Data Source -- TMY3
WMO Station 725340
- Using Design Conditions from "Climate Design Data 2009 ASHRAE Handbook"
- If the design condition source is ASHRAE, the design conditions are carefully generated
- from a period of record (typically 30 years) to be representative of that location and
- be suitable for use in heating/cooling load calculations. If the source is not ASHRAE,
- please consult the referenced source for the reasoning behind the data.
- Monthly Statistics for Dry Bulb temperatures °C
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
Maximum 16.0 15.5 23.8 26.0 29.0 34.0 40.0 34.0
34.0 31.0 24.0 14.0
Day:Hour 2:18 23:15 14:14 7:16 9:15 13:15 24:15 1:12
6:14 4:13 1:12 31:01
Minimum -21.0 -27.3 -11.2 3.0 4.0 9.0 15.0 15.0
10.0 2.0 -4.0 -18.0
Day:Hour 30:04 3:07 1:07 17:04 2:24 4:19 28:04 20:05
23:02 23:04 30:04 24:05
Daily Avg -5.7 -1.8 4.9 11.2 13.9 21.4 25.2 24.2
21.2 13.5 8.6 -0.8
- Maximum Dry Bulb temperature of 40.0°C on Jul 24
- Minimum Dry Bulb temperature of -27.3°C on Feb 3
- Average Hourly Statistics for Dry Bulb temperatures °C
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
0:01- 1:00 -5.9 -3.6 3.1 9.4 11.9 18.6 22.7 22.0
18.9 12.0 6.7 -1.7
1:01- 2:00 -6.1 -3.9 2.7 9.3 11.5 18.1 22.3 21.7
18.5 11.5 6.5 -1.9
2:01- 3:00 -6.3 -4.1 2.4 8.9 11.2 17.9 21.9 21.4
18.1 11.2 6.1 -2.0
3:01- 4:00 -6.7 -4.4 2.2 8.6 11.0 17.5 21.5 21.0
17.9 10.9 5.8 -2.4
4:01- 5:00 -7.0 -4.5 2.2 8.4 11.0 17.4 21.3 20.8
17.6 10.5 5.7 -2.7
5:01- 6:00 -7.2 -4.4 1.9 8.7 11.6 18.3 22.1 21.1
17.6 10.3 5.5 -2.8
182
6:01- 7:00 -7.5 -4.3 2.2 9.6 12.5 19.4 23.6 22.1
18.2 10.7 5.4 -2.9
7:01- 8:00 -7.4 -3.8 3.6 10.6 13.4 20.6 25.0 23.5
19.9 11.9 6.3 -2.5
8:01- 9:00 -7.2 -2.8 4.7 11.6 14.3 21.4 26.1 24.6
21.2 13.4 7.8 -1.7
9:01-10:00 -6.4 -1.5 5.9 12.2 15.0 22.5 26.9
25.6 22.3 14.6 9.4 -0.9
10:01-11:00 -5.7 -0.3 6.7 12.6 15.9 23.5 27.8
26.5 23.6 15.5 11.0 0.1
11:01-12:00 -5.0 0.5 7.2 13.3 16.6 23.8 28.7
27.2 24.4 15.9 12.0 0.7
12:01-13:00 -4.5 0.9 8.0 13.6 16.9 24.6 28.6
27.4 25.1 16.5 12.6 1.2
13:01-14:00 -4.2 1.4 8.3 14.0 17.2 25.0 28.7
27.6 25.2 16.9 12.9 1.3
14:01-15:00 -4.0 1.6 7.9 14.1 17.0 24.9 28.5
27.5 24.8 16.9 12.6 1.4
15:01-16:00 -4.1 1.2 7.8 13.9 16.6 24.7 28.2
27.4 24.6 16.4 12.0 1.1
16:01-17:00 -4.5 0.7 7.3 13.1 16.0 24.3 27.5
26.7 23.8 15.7 10.8 0.5
17:01-18:00 -4.6 -0.1 6.2 12.5 15.2 23.8 26.9
25.7 22.9 14.9 10.0 0.3
18:01-19:00 -4.7 -0.7 5.4 11.8 14.2 22.9 26.1
24.7 22.1 14.2 9.2 0.1
19:01-20:00 -5.0 -1.2 5.0 11.4 13.4 22.0 24.8
24.2 21.4 14.0 8.7 -0.1
20:01-21:00 -5.2 -1.7 4.6 10.8 12.9 21.3 24.4
23.6 20.8 13.3 8.2 -0.4
21:01-22:00 -5.5 -2.0 4.3 10.5 12.6 20.8 24.0
23.4 20.2 13.1 7.8 -0.8
22:01-23:00 -5.7 -2.6 4.0 10.2 12.4 20.3 23.7
22.9 19.8 12.7 7.4 -0.9
23:01-24:00 -6.1 -2.9 3.9 9.9 12.2 19.5 23.1
22.4 19.3 12.2 6.7 -1.4
Max Hour 15 15 14 15 14 14 14
14 14 15 14 15
Min Hour 7 5 6 5 5 5 5
5 6 6 7 7
- Monthly Statistics for Extreme temperatures °C
#Days Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
Max >= 32 4 8 6
4
Max <= 0 21 11 3
10
Min <= 0 30 19 12
5 21
Min <=-18 3 4
1
- Monthly Statistics for Dew Point temperatures °C
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
183
Maximum 13.0 15.5 12.7 18.3 20.0 23.0 24.4 24.0
23.0 20.0 14.0 11.0
Day:Hour 2:16 23:15 20:08 3:09 10:21 11:23 25:21 1:20
5:20 3:10 1:10 30:24
Minimum -26.0 -32.8 -18.9 -8.0 -8.0 6.0 7.0 7.0
3.0 -3.3 -12.0 -24.4
Day:Hour 30:03 3:01 2:05 24:20 2:19 3:07 2:11 18:10
23:10 15:15 30:13 24:09
Daily Avg -10.8 -6.8 -1.2 5.9 6.9 13.9 16.0 17.0
14.8 6.6 0.9 -6.0
- Maximum Dew Point temperature of 24.4°C on Jul 25
- Minimum Dew Point temperature of -32.8°C on Feb 3
- Monthly Statistics for Relative Humidity %
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
Maximum 100 100 100 100 100 100 94 94
100 94 100 100
Day:Hour 2:05 7:23 5:07 1:01 1:14 1:01 5:02 13:20
7:02 12:01 21:05 6:04
Minimum 31 25 25 24 25 26 25 28 31
20 15 34
Day:Hour 21:24 18:13 1:17 26:15 3:15 17:18 10:15 18:15
12:15 15:14 6:14 20:15
Daily Avg 65 68 66 73 65 65 59 66 69
65 60 67
- Average Hourly Relative Humidity %
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
0:01- 1:00 66 73 72 82 74 75 69 77
78 72 68 71
1:01- 2:00 66 73 74 82 74 77 70 78
79 73 69 71
2:01- 3:00 68 72 76 84 76 79 72 79
80 74 69 71
3:01- 4:00 67 75 77 86 77 81 73 79
80 74 69 71
4:01- 5:00 68 75 77 86 77 82 74 80
81 75 69 72
5:01- 6:00 68 75 77 85 75 79 71 79
81 76 69 71
6:01- 7:00 68 76 76 82 72 74 65 74
79 74 70 72
7:01- 8:00 69 75 71 76 68 70 59 68
73 70 68 71
8:01- 9:00 68 72 66 71 65 66 55 63
68 65 64 69
9:01-10:00 65 68 62 67 62 62 52
59 64 60 58 66
184
10:01-11:00 61 62 59 68 60 58 48
57 60 57 52 63
11:01-12:00 61 60 57 64 57 57 46
53 57 55 48 60
12:01-13:00 61 60 55 63 57 55 46
52 54 53 47 59
13:01-14:00 61 59 54 62 55 52 45
51 55 52 45 59
14:01-15:00 61 59 54 62 54 52 45
51 57 52 46 59
15:01-16:00 61 60 55 62 55 52 46
51 58 54 48 61
16:01-17:00 64 61 56 64 56 53 49
55 60 57 53 64
17:01-18:00 65 64 60 65 57 55 51
58 62 60 56 65
18:01-19:00 66 66 64 68 60 58 55
63 65 63 59 65
19:01-20:00 67 67 66 69 64 61 60
67 68 64 60 66
20:01-21:00 67 70 68 72 67 64 63
71 70 67 61 67
21:01-22:00 66 70 69 75 68 67 65
72 72 68 62 68
22:01-23:00 66 72 71 78 69 70 66
74 74 69 63 68
23:01-24:00 65 72 72 80 71 72 69
76 76 71 66 70
Max Hour 8 7 5 5 4 5 5
5 6 6 7 7
Min Hour 12 15 14 14 15 15 15
15 13 15 14 15
- Monthly Indicators for Precipitation/Moisture (kPa)
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
0.3 0.5 0.6 1.0 1.1 1.6 1.7 1.9
1.8 1.0 0.7 0.5
- Monthly Statistics for Wind Chill/Heat Index temperatures °C **
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
Minimum WC -37 -46 -25 -8 -5 2
-5 -12 -37
Day:Hour 6:09 3:07 1:07 16:09 2:06 4:19
25:07 29:09 19:08
Average WC -16 -13 -4 2 2 5
3 0 -10
Avg Del WC 10 10 7 6 5 4
4 5 8
# Hours WC 723 613 557 270 92 4
194 418 679
Maximum HI 28 37 40
39 39 32
185
Day:Hour 9:14 13:15 24:11 1:16
6:14 4:13
Average HI 28 30 30
31 31 29
Avg Del HI 1 1 1
2 2 1
# Hours HI 2 133 186
165 75 34
- **WindChill/HeatIndex Temps -- statistics...only those different from Air Temps
- Monthly Wind Direction % {N=0 or 360,E=90,S=180,W=270}
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
North 9 11 16 15 27 7 16 10
17 20 14 9
NorthEast 6 9 14 23 21 11 21 20
10 8 3 1
East 8 2 10 23 17 11 16 20
9 10 3 3
SouthEast 8 2 2 11 7 7 4 8
4 3 3 3
South 7 7 11 10 5 17 10 9
11 15 15 14
SouthWest 13 19 13 6 3 24 14 19
25 16 26 22
West 22 24 14 6 10 15 13 10
14 9 17 21
NorthWest 26 26 19 7 10 8 6 4
10 19 21 26
- Monthly Statistics for Wind Speed m/s
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
Maximum 11.3 11.8 12.8 14.9 17.0 9.8 11.3 10.8
11.3 9.8 11.3 15.4
Day:Hour 14:16 11:06 20:15 6:14 11:12 15:12 20:13 22:01
6:21 19:10 10:24 12:18
Minimum 0.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0
0.0 0.0 0.0 0.0
Day:Hour 1:02 6:05 3:03 7:04 4:02 8:03 9:01 3:11
2:23 2:16 1:04 2:09
Daily Avg 5.2 5.6 4.7 4.9 4.9 3.9 4.0 4.0
3.6 4.2 4.3 5.2
- Maximum Wind Speed of 17.0 m/s on May 11
- Minimum Wind Speed of 0.0 m/s on Jan 1
- Monthly Statistics for Liquid Precipitation mm
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
Total 17 11 38 141 128 46 44 66 57
12 10 27
186
- Monthly Statistics for Albedo
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
Average 0.170 0.160 0.150 0.160 0.170 0.160 0.150 0.150
0.180 0.160 0.170 0.180
- Monthly Statistics for Solar Radiation (Direct Normal, Diffuse, Global Horizontal) Wh/m²
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
Direct Avg 2082 2670 2734 3407 4330 4813 5124
4735 4552 3024 3424 2675
Direct Max 5848 7837 8544 8726 8720 8651 8585
8009 7757 6722 5259 5035
Day 19 24 3 30 22 17 8 7
4 1 4 29
Diffuse Avg 936 1118 1572 1951 2454 2646 2642
2251 1791 1391 1017 772
Global Avg 1649 2236 3003 4066 5413 5985 6196
5373 4451 2832 2341 1644
- Maximum Direct Normal Solar of 8726 Wh/m² on Apr 30
- Average Hourly Statistics for Direct Normal Solar Radiation Wh/m²
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
0:01- 1:00 0 0 0 0 0 0 0 0
0 0 0 0
1:01- 2:00 0 0 0 0 0 0 0 0
0 0 0 0
2:01- 3:00 0 0 0 0 0 0 0 0
0 0 0 0
3:01- 4:00 0 0 0 0 0 0 0 0
0 0 0 0
4:01- 5:00 0 0 0 0 12 43 13 0
0 0 0 0
5:01- 6:00 0 0 1 24 94 146 114 16
17 0 0 0
6:01- 7:00 0 3 66 216 202 247 282 216
142 37 9 0
7:01- 8:00 40 108 217 273 202 305 370 338
309 240 145 30
8:01- 9:00 191 234 282 328 281 370 434 401
402 342 353 263
9:01-10:00 213 305 302 328 299 425 433
449 445 337 422 330
10:01-11:00 254 334 304 345 375 402 515
490 460 350 491 387
11:01-12:00 310 311 328 326 457 418 487
444 505 374 507 426
12:01-13:00 301 313 314 285 446 459 513
495 465 352 478 388
13:01-14:00 229 335 291 303 450 448 424
453 487 301 437 334
187
14:01-15:00 257 310 250 299 425 408 430
422 476 276 359 307
15:01-16:00 219 280 204 289 402 379 395
395 441 291 212 210
16:01-17:00 68 129 140 225 332 335 305
348 299 123 10 0
17:01-18:00 0 9 36 157 259 273 265
221 105 0 0 0
18:01-19:00 0 0 0 8 93 156 145
48 0 0 0 0
19:01-20:00 0 0 0 0 0 0 0
0 0 0 0 0
20:01-21:00 0 0 0 0 0 0 0
0 0 0 0 0
21:01-22:00 0 0 0 0 0 0 0
0 0 0 0 0
22:01-23:00 0 0 0 0 0 0 0
0 0 0 0 0
23:01-24:00 0 0 0 0 0 0 0
0 0 0 0 0
Max Hour* 12 14 12 11* 12 13 11*
13 12 12 12 12
Min Hour 1 1 1 1 1 1 1
1 1 1 1 1
- Monthly Calculated "undisturbed" Ground Temperatures** °C
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
0.5 m 3.4 -1.4 -2.7 -1.5 4.9 12.1 18.9 23.8
25.3 23.0 17.4 10.4
2.0 m 7.7 3.2 1.1 1.0 4.4 9.4 14.7 19.2
21.6 21.2 18.0 13.2
4.0 m 10.5 7.0 4.9 4.3 5.5 8.4 12.0 15.5
17.8 18.4 17.0 14.2
- **These ground temperatures should NOT BE USED in the GroundTemperatures object to compute building
floor losses.
- The temperatures for 0.5 m depth can be used for GroundTemperatures:Surface.
- The temperatures for 4.0 m depth can be used for GroundTemperatures:Deep.
- Calculations use a standard soil diffusivity of 2.3225760E-03 {m**2/day}
- Monthly Heating/Cooling Degree Days/Hours
Jan Feb Mar Apr May Jun Jul Aug
Sep Oct Nov Dec
HDD base 10C 487 330 179 22 4 0 0
0 0 19 83 334
HDD base 18C 734 554 406 206 133 36 0
0 7 166 281 581
CDD base 10C 1 0 21 59 123 341 471
441 335 129 43 0
CDD base 18C 0 0 0 2 5 138 223
193 103 28 0 0
CDH base 20C 0 0 32 80 146 2528 3997
3239 1759 562 65 0
188
CDH base 23C 0 0 1 13 34 1396 2185
1531 773 246 2 0
CDH base 27C 0 0 0 0 6 433 665
417 216 51 0 0
- 1964 annual cooling degree-days (10°C baseline)
- 1458 annual heating degree-days (10°C baseline)
- 691 annual cooling degree-days (18°C baseline)
- 3106 annual heating degree-days (18°C baseline)
- Climate type "Dfa" (Köppen classification)**
- Humid continental (hot summer, cold winter, no dry season, lat. 30-60°N)
- Unbearably hot dry periods in summer, but passive cooling is possible
- **Note that the Köppen classification shown here is derived algorithmically from the source weather data.
- It may not be indicative of the long term climate for this location.
- Climate type "5A" (ASHRAE Standards 90.1-2004 and 90.2-2004 Climate Zone)**
- Cool - Humid, Probable Köppen classification=Dfa, Humid Continental (Warm Summer)
- **Note that the ASHRAE classification shown here is derived algorithmically from the source weather data.
- It may not be indicative of the long term climate for this location.
- Typical/Extreme Period Determination
- Summer is Jun:Aug
Extreme Summer Week (nearest maximum temperature for summer)
Extreme Hot Week Period selected: Jul 20:Jul 26, Maximum Temp= 40.00°C, Deviation=|12.812|°C
Typical Summer Week (nearest average temperature for summer)
Typical Week Period selected: Aug 24:Aug 30, Average Temp= 23.62°C, Deviation=| 0.079|°C
- Winter is Dec:Feb
Extreme Winter Week (nearest minimum temperature for winter)
Extreme Cold Week Period selected: Jan 27:Feb 2, Minimum Temp= -27.30°C, Deviation=|11.760|°C
Typical Winter Week (nearest average temperature for winter)
Typical Week Period selected: Dec 15:Dec 21, Average Temp= -2.77°C, Deviation=| 0.655|°C
- Autumn is Sep:Nov
Typical Autumn Week (nearest average temperature for autumn)
Typical Week Period selected: Oct 13:Oct 19, Average Temp= 14.45°C, Deviation=| 0.597|°C
- Spring is Mar:May
Typical Spring Week (nearest average temperature for spring)
Typical Week Period selected: Apr 19:Apr 25, Average Temp= 9.97°C, Deviation=| 0.303|°C
189
APPENDIX C: DesignBuilder’s input -Shaft-corridor type facade
Activity settings
190
Opening settings
191
HVAC setting
192
Lightings
For the other alternatives just the geometry has been changed, the rest of the inputs remains the
same.
193
APPENDIX D: PMV graphs of all 36 simulations
General parameters: One parameter constant and show the correlation for the other two
parameters
194
195
196
197
198
APPENDIX E: Impact of parameters on cooling and heating energy
199
200
201
202
203
204
205
206
207
